mirror of
https://github.com/bmad-labs/skills.git
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#Init Skill
This commit is contained in:
mti-tannt
@@ -0,0 +1,23 @@
|
||||
{
|
||||
"name": "bmad-skills",
|
||||
"owner": {
|
||||
"name": "thuantan2060",
|
||||
"email": "thuantan2060@gmail.com"
|
||||
},
|
||||
"metadata": {
|
||||
"description": "BMAD Skills Marketplace - Custom skills for Claude Code",
|
||||
"version": "1.0.0"
|
||||
},
|
||||
"plugins": [
|
||||
{
|
||||
"name": "bmad-skills",
|
||||
"description": "Collection of skills including skill creation tools and MCP server development guides",
|
||||
"source": "./",
|
||||
"strict": false,
|
||||
"skills": [
|
||||
"./skills/skill-creator",
|
||||
"./skills/mcp-builder"
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
+43
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|
||||
# OS files
|
||||
.DS_Store
|
||||
Thumbs.db
|
||||
|
||||
# IDE/Editor
|
||||
.idea/
|
||||
.vscode/
|
||||
*.swp
|
||||
*.swo
|
||||
*~
|
||||
|
||||
# Python
|
||||
__pycache__/
|
||||
*.py[cod]
|
||||
*$py.class
|
||||
.Python
|
||||
venv/
|
||||
env/
|
||||
.env
|
||||
|
||||
# Node
|
||||
node_modules/
|
||||
npm-debug.log
|
||||
yarn-error.log
|
||||
|
||||
# Build outputs
|
||||
dist/
|
||||
build/
|
||||
*.egg-info/
|
||||
|
||||
# Testing
|
||||
.coverage
|
||||
.pytest_cache/
|
||||
htmlcov/
|
||||
|
||||
# Logs
|
||||
*.log
|
||||
logs/
|
||||
|
||||
# Temporary files
|
||||
tmp/
|
||||
temp/
|
||||
*.tmp
|
||||
+112
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|
||||
# Contributing to BMAD Skills
|
||||
|
||||
Thank you for your interest in contributing to the BMAD Skills marketplace!
|
||||
|
||||
## Creating a New Skill
|
||||
|
||||
### Step 1: Plan Your Skill
|
||||
|
||||
Before creating a skill, consider:
|
||||
|
||||
- **Purpose**: What specific problem does this skill solve?
|
||||
- **Audience**: Who will use this skill?
|
||||
- **Scope**: Keep skills focused on a single domain or task
|
||||
- **Value**: Does this add capabilities Claude doesn't already have?
|
||||
|
||||
### Step 2: Set Up Your Skill
|
||||
|
||||
1. Copy the template:
|
||||
```bash
|
||||
cp -r template/ skills/your-skill-name/
|
||||
```
|
||||
|
||||
2. Rename and edit `SKILL.md`:
|
||||
- Set a unique, descriptive `name` in the frontmatter
|
||||
- Write a clear `description` explaining when to use the skill
|
||||
- Add detailed instructions and examples
|
||||
|
||||
### Step 3: Structure Your Skill
|
||||
|
||||
```
|
||||
your-skill-name/
|
||||
├── SKILL.md # Required - Main definition
|
||||
├── scripts/ # Optional - Helper scripts
|
||||
├── references/ # Optional - Reference docs
|
||||
└── assets/ # Optional - Resources
|
||||
```
|
||||
|
||||
### Step 4: Write the SKILL.md
|
||||
|
||||
#### Frontmatter (Required)
|
||||
|
||||
```yaml
|
||||
---
|
||||
name: your-skill-name
|
||||
description: A complete description of what this skill does and when Claude should use it.
|
||||
---
|
||||
```
|
||||
|
||||
#### Content Guidelines
|
||||
|
||||
- **Be Specific**: Provide concrete instructions, not vague guidelines
|
||||
- **Include Examples**: Show actual input/output scenarios
|
||||
- **Stay Focused**: One skill = one domain or task
|
||||
- **Keep It Concise**: Aim for under 500 lines
|
||||
- **Reference Resources**: Link to scripts/docs instead of inlining large content
|
||||
|
||||
### Step 5: Test Your Skill
|
||||
|
||||
1. Install locally in Claude Code:
|
||||
```json
|
||||
{
|
||||
"skills": ["/path/to/bmad-skills/skills/your-skill-name"]
|
||||
}
|
||||
```
|
||||
|
||||
2. Test various scenarios:
|
||||
- Does Claude invoke the skill appropriately?
|
||||
- Are the instructions clear and actionable?
|
||||
- Do examples cover common use cases?
|
||||
|
||||
### Step 6: Submit Your Skill
|
||||
|
||||
1. Create a branch: `git checkout -b skill/your-skill-name`
|
||||
2. Add your skill files
|
||||
3. Update the README.md skills table
|
||||
4. Submit a pull request
|
||||
|
||||
## Skill Quality Checklist
|
||||
|
||||
- [ ] `name` is lowercase, hyphenated, and unique
|
||||
- [ ] `description` clearly explains purpose and use cases
|
||||
- [ ] Instructions are specific and actionable
|
||||
- [ ] Examples demonstrate real usage scenarios
|
||||
- [ ] No sensitive data or credentials included
|
||||
- [ ] Scripts are well-commented and functional
|
||||
- [ ] Tested locally with Claude Code
|
||||
|
||||
## Code Style
|
||||
|
||||
### SKILL.md
|
||||
|
||||
- Use clear, imperative language
|
||||
- Structure with headers and lists
|
||||
- Include code blocks with language hints
|
||||
- Keep paragraphs short
|
||||
|
||||
### Scripts
|
||||
|
||||
- Include shebang and encoding declarations
|
||||
- Add docstrings/comments explaining purpose
|
||||
- Handle errors gracefully
|
||||
- Follow language conventions (PEP 8, etc.)
|
||||
|
||||
## Getting Help
|
||||
|
||||
- Open an issue for questions
|
||||
- Tag maintainers for review
|
||||
- Check existing skills for examples
|
||||
|
||||
## License
|
||||
|
||||
By contributing, you agree that your contributions will be licensed under the same license as this repository.
|
||||
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|
||||
# BMAD Skills Marketplace
|
||||
|
||||
A collection of skills for Claude Code that extend its capabilities with specialized knowledge and workflows.
|
||||
|
||||
## What are Skills?
|
||||
|
||||
Skills are self-contained instruction sets that teach Claude Code how to perform specialized tasks. Each skill is defined in a `SKILL.md` file with optional supporting resources like scripts, templates, and reference documentation.
|
||||
|
||||
## Repository Structure
|
||||
|
||||
```
|
||||
bmad-skills/
|
||||
├── skills/ # All skill implementations
|
||||
│ └── [skill-name]/ # Individual skill folder
|
||||
│ ├── SKILL.md # Required - Main skill definition
|
||||
│ ├── scripts/ # Optional - Supporting scripts
|
||||
│ ├── references/ # Optional - Reference documentation
|
||||
│ └── assets/ # Optional - Images, resources
|
||||
├── template/ # Starter template for new skills
|
||||
├── spec/ # Skills specification documentation
|
||||
├── CONTRIBUTING.md # Contribution guidelines
|
||||
└── README.md # This file
|
||||
```
|
||||
|
||||
## Using Skills
|
||||
|
||||
### Installing a Skill
|
||||
|
||||
To use a skill in Claude Code, add it to your project's `.claude/settings.json`:
|
||||
|
||||
```json
|
||||
{
|
||||
"skills": [
|
||||
"github:bmad-labs/skills/skills/skill-name"
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
Or install from a local path during development:
|
||||
|
||||
```json
|
||||
{
|
||||
"skills": [
|
||||
"/path/to/bmad-skills/skills/skill-name"
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
### Invoking a Skill
|
||||
|
||||
Once installed, you can invoke skills using the slash command format:
|
||||
|
||||
```
|
||||
/skill-name [arguments]
|
||||
```
|
||||
|
||||
Or simply describe what you need - Claude will automatically use relevant skills.
|
||||
|
||||
## Creating New Skills
|
||||
|
||||
1. Copy the `template/` folder to `skills/your-skill-name/`
|
||||
2. Edit `SKILL.md` with your skill definition
|
||||
3. Add any supporting scripts or references
|
||||
4. Test the skill locally
|
||||
5. Submit a PR
|
||||
|
||||
See [CONTRIBUTING.md](CONTRIBUTING.md) for detailed guidelines.
|
||||
|
||||
## Skill Categories
|
||||
|
||||
| Category | Description |
|
||||
|----------|-------------|
|
||||
| Development | Coding, architecture, testing, DevOps |
|
||||
| Productivity | Documents, project management, workflows |
|
||||
| Creative | Design, content creation, branding |
|
||||
| Data | Processing, analysis, visualization |
|
||||
|
||||
## Available Skills
|
||||
|
||||
| Skill | Description | Category |
|
||||
|-------|-------------|----------|
|
||||
| [skill-creator](skills/skill-creator) | Guide for creating effective skills that extend Claude's capabilities | Development |
|
||||
| [mcp-builder](skills/mcp-builder) | Guide for creating high-quality MCP servers for LLM integrations | Development |
|
||||
|
||||
## License
|
||||
|
||||
MIT License - See individual skills for specific licensing.
|
||||
@@ -0,0 +1,202 @@
|
||||
|
||||
Apache License
|
||||
Version 2.0, January 2004
|
||||
http://www.apache.org/licenses/
|
||||
|
||||
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
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@@ -0,0 +1,236 @@
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||||
---
|
||||
name: mcp-builder
|
||||
description: Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
|
||||
license: Complete terms in LICENSE.txt
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---
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||||
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||||
# MCP Server Development Guide
|
||||
|
||||
## Overview
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||||
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||||
Create MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. The quality of an MCP server is measured by how well it enables LLMs to accomplish real-world tasks.
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||||
|
||||
---
|
||||
|
||||
# Process
|
||||
|
||||
## 🚀 High-Level Workflow
|
||||
|
||||
Creating a high-quality MCP server involves four main phases:
|
||||
|
||||
### Phase 1: Deep Research and Planning
|
||||
|
||||
#### 1.1 Understand Modern MCP Design
|
||||
|
||||
**API Coverage vs. Workflow Tools:**
|
||||
Balance comprehensive API endpoint coverage with specialized workflow tools. Workflow tools can be more convenient for specific tasks, while comprehensive coverage gives agents flexibility to compose operations. Performance varies by client—some clients benefit from code execution that combines basic tools, while others work better with higher-level workflows. When uncertain, prioritize comprehensive API coverage.
|
||||
|
||||
**Tool Naming and Discoverability:**
|
||||
Clear, descriptive tool names help agents find the right tools quickly. Use consistent prefixes (e.g., `github_create_issue`, `github_list_repos`) and action-oriented naming.
|
||||
|
||||
**Context Management:**
|
||||
Agents benefit from concise tool descriptions and the ability to filter/paginate results. Design tools that return focused, relevant data. Some clients support code execution which can help agents filter and process data efficiently.
|
||||
|
||||
**Actionable Error Messages:**
|
||||
Error messages should guide agents toward solutions with specific suggestions and next steps.
|
||||
|
||||
#### 1.2 Study MCP Protocol Documentation
|
||||
|
||||
**Navigate the MCP specification:**
|
||||
|
||||
Start with the sitemap to find relevant pages: `https://modelcontextprotocol.io/sitemap.xml`
|
||||
|
||||
Then fetch specific pages with `.md` suffix for markdown format (e.g., `https://modelcontextprotocol.io/specification/draft.md`).
|
||||
|
||||
Key pages to review:
|
||||
- Specification overview and architecture
|
||||
- Transport mechanisms (streamable HTTP, stdio)
|
||||
- Tool, resource, and prompt definitions
|
||||
|
||||
#### 1.3 Study Framework Documentation
|
||||
|
||||
**Recommended stack:**
|
||||
- **Language**: TypeScript (high-quality SDK support and good compatibility in many execution environments e.g. MCPB. Plus AI models are good at generating TypeScript code, benefiting from its broad usage, static typing and good linting tools)
|
||||
- **Transport**: Streamable HTTP for remote servers, using stateless JSON (simpler to scale and maintain, as opposed to stateful sessions and streaming responses). stdio for local servers.
|
||||
|
||||
**Load framework documentation:**
|
||||
|
||||
- **MCP Best Practices**: [📋 View Best Practices](./reference/mcp_best_practices.md) - Core guidelines
|
||||
|
||||
**For TypeScript (recommended):**
|
||||
- **TypeScript SDK**: Use WebFetch to load `https://raw.githubusercontent.com/modelcontextprotocol/typescript-sdk/main/README.md`
|
||||
- [⚡ TypeScript Guide](./reference/node_mcp_server.md) - TypeScript patterns and examples
|
||||
|
||||
**For Python:**
|
||||
- **Python SDK**: Use WebFetch to load `https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md`
|
||||
- [🐍 Python Guide](./reference/python_mcp_server.md) - Python patterns and examples
|
||||
|
||||
#### 1.4 Plan Your Implementation
|
||||
|
||||
**Understand the API:**
|
||||
Review the service's API documentation to identify key endpoints, authentication requirements, and data models. Use web search and WebFetch as needed.
|
||||
|
||||
**Tool Selection:**
|
||||
Prioritize comprehensive API coverage. List endpoints to implement, starting with the most common operations.
|
||||
|
||||
---
|
||||
|
||||
### Phase 2: Implementation
|
||||
|
||||
#### 2.1 Set Up Project Structure
|
||||
|
||||
See language-specific guides for project setup:
|
||||
- [⚡ TypeScript Guide](./reference/node_mcp_server.md) - Project structure, package.json, tsconfig.json
|
||||
- [🐍 Python Guide](./reference/python_mcp_server.md) - Module organization, dependencies
|
||||
|
||||
#### 2.2 Implement Core Infrastructure
|
||||
|
||||
Create shared utilities:
|
||||
- API client with authentication
|
||||
- Error handling helpers
|
||||
- Response formatting (JSON/Markdown)
|
||||
- Pagination support
|
||||
|
||||
#### 2.3 Implement Tools
|
||||
|
||||
For each tool:
|
||||
|
||||
**Input Schema:**
|
||||
- Use Zod (TypeScript) or Pydantic (Python)
|
||||
- Include constraints and clear descriptions
|
||||
- Add examples in field descriptions
|
||||
|
||||
**Output Schema:**
|
||||
- Define `outputSchema` where possible for structured data
|
||||
- Use `structuredContent` in tool responses (TypeScript SDK feature)
|
||||
- Helps clients understand and process tool outputs
|
||||
|
||||
**Tool Description:**
|
||||
- Concise summary of functionality
|
||||
- Parameter descriptions
|
||||
- Return type schema
|
||||
|
||||
**Implementation:**
|
||||
- Async/await for I/O operations
|
||||
- Proper error handling with actionable messages
|
||||
- Support pagination where applicable
|
||||
- Return both text content and structured data when using modern SDKs
|
||||
|
||||
**Annotations:**
|
||||
- `readOnlyHint`: true/false
|
||||
- `destructiveHint`: true/false
|
||||
- `idempotentHint`: true/false
|
||||
- `openWorldHint`: true/false
|
||||
|
||||
---
|
||||
|
||||
### Phase 3: Review and Test
|
||||
|
||||
#### 3.1 Code Quality
|
||||
|
||||
Review for:
|
||||
- No duplicated code (DRY principle)
|
||||
- Consistent error handling
|
||||
- Full type coverage
|
||||
- Clear tool descriptions
|
||||
|
||||
#### 3.2 Build and Test
|
||||
|
||||
**TypeScript:**
|
||||
- Run `npm run build` to verify compilation
|
||||
- Test with MCP Inspector: `npx @modelcontextprotocol/inspector`
|
||||
|
||||
**Python:**
|
||||
- Verify syntax: `python -m py_compile your_server.py`
|
||||
- Test with MCP Inspector
|
||||
|
||||
See language-specific guides for detailed testing approaches and quality checklists.
|
||||
|
||||
---
|
||||
|
||||
### Phase 4: Create Evaluations
|
||||
|
||||
After implementing your MCP server, create comprehensive evaluations to test its effectiveness.
|
||||
|
||||
**Load [✅ Evaluation Guide](./reference/evaluation.md) for complete evaluation guidelines.**
|
||||
|
||||
#### 4.1 Understand Evaluation Purpose
|
||||
|
||||
Use evaluations to test whether LLMs can effectively use your MCP server to answer realistic, complex questions.
|
||||
|
||||
#### 4.2 Create 10 Evaluation Questions
|
||||
|
||||
To create effective evaluations, follow the process outlined in the evaluation guide:
|
||||
|
||||
1. **Tool Inspection**: List available tools and understand their capabilities
|
||||
2. **Content Exploration**: Use READ-ONLY operations to explore available data
|
||||
3. **Question Generation**: Create 10 complex, realistic questions
|
||||
4. **Answer Verification**: Solve each question yourself to verify answers
|
||||
|
||||
#### 4.3 Evaluation Requirements
|
||||
|
||||
Ensure each question is:
|
||||
- **Independent**: Not dependent on other questions
|
||||
- **Read-only**: Only non-destructive operations required
|
||||
- **Complex**: Requiring multiple tool calls and deep exploration
|
||||
- **Realistic**: Based on real use cases humans would care about
|
||||
- **Verifiable**: Single, clear answer that can be verified by string comparison
|
||||
- **Stable**: Answer won't change over time
|
||||
|
||||
#### 4.4 Output Format
|
||||
|
||||
Create an XML file with this structure:
|
||||
|
||||
```xml
|
||||
<evaluation>
|
||||
<qa_pair>
|
||||
<question>Find discussions about AI model launches with animal codenames. One model needed a specific safety designation that uses the format ASL-X. What number X was being determined for the model named after a spotted wild cat?</question>
|
||||
<answer>3</answer>
|
||||
</qa_pair>
|
||||
<!-- More qa_pairs... -->
|
||||
</evaluation>
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
# Reference Files
|
||||
|
||||
## 📚 Documentation Library
|
||||
|
||||
Load these resources as needed during development:
|
||||
|
||||
### Core MCP Documentation (Load First)
|
||||
- **MCP Protocol**: Start with sitemap at `https://modelcontextprotocol.io/sitemap.xml`, then fetch specific pages with `.md` suffix
|
||||
- [📋 MCP Best Practices](./reference/mcp_best_practices.md) - Universal MCP guidelines including:
|
||||
- Server and tool naming conventions
|
||||
- Response format guidelines (JSON vs Markdown)
|
||||
- Pagination best practices
|
||||
- Transport selection (streamable HTTP vs stdio)
|
||||
- Security and error handling standards
|
||||
|
||||
### SDK Documentation (Load During Phase 1/2)
|
||||
- **Python SDK**: Fetch from `https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md`
|
||||
- **TypeScript SDK**: Fetch from `https://raw.githubusercontent.com/modelcontextprotocol/typescript-sdk/main/README.md`
|
||||
|
||||
### Language-Specific Implementation Guides (Load During Phase 2)
|
||||
- [🐍 Python Implementation Guide](./reference/python_mcp_server.md) - Complete Python/FastMCP guide with:
|
||||
- Server initialization patterns
|
||||
- Pydantic model examples
|
||||
- Tool registration with `@mcp.tool`
|
||||
- Complete working examples
|
||||
- Quality checklist
|
||||
|
||||
- [⚡ TypeScript Implementation Guide](./reference/node_mcp_server.md) - Complete TypeScript guide with:
|
||||
- Project structure
|
||||
- Zod schema patterns
|
||||
- Tool registration with `server.registerTool`
|
||||
- Complete working examples
|
||||
- Quality checklist
|
||||
|
||||
### Evaluation Guide (Load During Phase 4)
|
||||
- [✅ Evaluation Guide](./reference/evaluation.md) - Complete evaluation creation guide with:
|
||||
- Question creation guidelines
|
||||
- Answer verification strategies
|
||||
- XML format specifications
|
||||
- Example questions and answers
|
||||
- Running an evaluation with the provided scripts
|
||||
@@ -0,0 +1,602 @@
|
||||
# MCP Server Evaluation Guide
|
||||
|
||||
## Overview
|
||||
|
||||
This document provides guidance on creating comprehensive evaluations for MCP servers. Evaluations test whether LLMs can effectively use your MCP server to answer realistic, complex questions using only the tools provided.
|
||||
|
||||
---
|
||||
|
||||
## Quick Reference
|
||||
|
||||
### Evaluation Requirements
|
||||
- Create 10 human-readable questions
|
||||
- Questions must be READ-ONLY, INDEPENDENT, NON-DESTRUCTIVE
|
||||
- Each question requires multiple tool calls (potentially dozens)
|
||||
- Answers must be single, verifiable values
|
||||
- Answers must be STABLE (won't change over time)
|
||||
|
||||
### Output Format
|
||||
```xml
|
||||
<evaluation>
|
||||
<qa_pair>
|
||||
<question>Your question here</question>
|
||||
<answer>Single verifiable answer</answer>
|
||||
</qa_pair>
|
||||
</evaluation>
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Purpose of Evaluations
|
||||
|
||||
The measure of quality of an MCP server is NOT how well or comprehensively the server implements tools, but how well these implementations (input/output schemas, docstrings/descriptions, functionality) enable LLMs with no other context and access ONLY to the MCP servers to answer realistic and difficult questions.
|
||||
|
||||
## Evaluation Overview
|
||||
|
||||
Create 10 human-readable questions requiring ONLY READ-ONLY, INDEPENDENT, NON-DESTRUCTIVE, and IDEMPOTENT operations to answer. Each question should be:
|
||||
- Realistic
|
||||
- Clear and concise
|
||||
- Unambiguous
|
||||
- Complex, requiring potentially dozens of tool calls or steps
|
||||
- Answerable with a single, verifiable value that you identify in advance
|
||||
|
||||
## Question Guidelines
|
||||
|
||||
### Core Requirements
|
||||
|
||||
1. **Questions MUST be independent**
|
||||
- Each question should NOT depend on the answer to any other question
|
||||
- Should not assume prior write operations from processing another question
|
||||
|
||||
2. **Questions MUST require ONLY NON-DESTRUCTIVE AND IDEMPOTENT tool use**
|
||||
- Should not instruct or require modifying state to arrive at the correct answer
|
||||
|
||||
3. **Questions must be REALISTIC, CLEAR, CONCISE, and COMPLEX**
|
||||
- Must require another LLM to use multiple (potentially dozens of) tools or steps to answer
|
||||
|
||||
### Complexity and Depth
|
||||
|
||||
4. **Questions must require deep exploration**
|
||||
- Consider multi-hop questions requiring multiple sub-questions and sequential tool calls
|
||||
- Each step should benefit from information found in previous questions
|
||||
|
||||
5. **Questions may require extensive paging**
|
||||
- May need paging through multiple pages of results
|
||||
- May require querying old data (1-2 years out-of-date) to find niche information
|
||||
- The questions must be DIFFICULT
|
||||
|
||||
6. **Questions must require deep understanding**
|
||||
- Rather than surface-level knowledge
|
||||
- May pose complex ideas as True/False questions requiring evidence
|
||||
- May use multiple-choice format where LLM must search different hypotheses
|
||||
|
||||
7. **Questions must not be solvable with straightforward keyword search**
|
||||
- Do not include specific keywords from the target content
|
||||
- Use synonyms, related concepts, or paraphrases
|
||||
- Require multiple searches, analyzing multiple related items, extracting context, then deriving the answer
|
||||
|
||||
### Tool Testing
|
||||
|
||||
8. **Questions should stress-test tool return values**
|
||||
- May elicit tools returning large JSON objects or lists, overwhelming the LLM
|
||||
- Should require understanding multiple modalities of data:
|
||||
- IDs and names
|
||||
- Timestamps and datetimes (months, days, years, seconds)
|
||||
- File IDs, names, extensions, and mimetypes
|
||||
- URLs, GIDs, etc.
|
||||
- Should probe the tool's ability to return all useful forms of data
|
||||
|
||||
9. **Questions should MOSTLY reflect real human use cases**
|
||||
- The kinds of information retrieval tasks that HUMANS assisted by an LLM would care about
|
||||
|
||||
10. **Questions may require dozens of tool calls**
|
||||
- This challenges LLMs with limited context
|
||||
- Encourages MCP server tools to reduce information returned
|
||||
|
||||
11. **Include ambiguous questions**
|
||||
- May be ambiguous OR require difficult decisions on which tools to call
|
||||
- Force the LLM to potentially make mistakes or misinterpret
|
||||
- Ensure that despite AMBIGUITY, there is STILL A SINGLE VERIFIABLE ANSWER
|
||||
|
||||
### Stability
|
||||
|
||||
12. **Questions must be designed so the answer DOES NOT CHANGE**
|
||||
- Do not ask questions that rely on "current state" which is dynamic
|
||||
- For example, do not count:
|
||||
- Number of reactions to a post
|
||||
- Number of replies to a thread
|
||||
- Number of members in a channel
|
||||
|
||||
13. **DO NOT let the MCP server RESTRICT the kinds of questions you create**
|
||||
- Create challenging and complex questions
|
||||
- Some may not be solvable with the available MCP server tools
|
||||
- Questions may require specific output formats (datetime vs. epoch time, JSON vs. MARKDOWN)
|
||||
- Questions may require dozens of tool calls to complete
|
||||
|
||||
## Answer Guidelines
|
||||
|
||||
### Verification
|
||||
|
||||
1. **Answers must be VERIFIABLE via direct string comparison**
|
||||
- If the answer can be re-written in many formats, clearly specify the output format in the QUESTION
|
||||
- Examples: "Use YYYY/MM/DD.", "Respond True or False.", "Answer A, B, C, or D and nothing else."
|
||||
- Answer should be a single VERIFIABLE value such as:
|
||||
- User ID, user name, display name, first name, last name
|
||||
- Channel ID, channel name
|
||||
- Message ID, string
|
||||
- URL, title
|
||||
- Numerical quantity
|
||||
- Timestamp, datetime
|
||||
- Boolean (for True/False questions)
|
||||
- Email address, phone number
|
||||
- File ID, file name, file extension
|
||||
- Multiple choice answer
|
||||
- Answers must not require special formatting or complex, structured output
|
||||
- Answer will be verified using DIRECT STRING COMPARISON
|
||||
|
||||
### Readability
|
||||
|
||||
2. **Answers should generally prefer HUMAN-READABLE formats**
|
||||
- Examples: names, first name, last name, datetime, file name, message string, URL, yes/no, true/false, a/b/c/d
|
||||
- Rather than opaque IDs (though IDs are acceptable)
|
||||
- The VAST MAJORITY of answers should be human-readable
|
||||
|
||||
### Stability
|
||||
|
||||
3. **Answers must be STABLE/STATIONARY**
|
||||
- Look at old content (e.g., conversations that have ended, projects that have launched, questions answered)
|
||||
- Create QUESTIONS based on "closed" concepts that will always return the same answer
|
||||
- Questions may ask to consider a fixed time window to insulate from non-stationary answers
|
||||
- Rely on context UNLIKELY to change
|
||||
- Example: if finding a paper name, be SPECIFIC enough so answer is not confused with papers published later
|
||||
|
||||
4. **Answers must be CLEAR and UNAMBIGUOUS**
|
||||
- Questions must be designed so there is a single, clear answer
|
||||
- Answer can be derived from using the MCP server tools
|
||||
|
||||
### Diversity
|
||||
|
||||
5. **Answers must be DIVERSE**
|
||||
- Answer should be a single VERIFIABLE value in diverse modalities and formats
|
||||
- User concept: user ID, user name, display name, first name, last name, email address, phone number
|
||||
- Channel concept: channel ID, channel name, channel topic
|
||||
- Message concept: message ID, message string, timestamp, month, day, year
|
||||
|
||||
6. **Answers must NOT be complex structures**
|
||||
- Not a list of values
|
||||
- Not a complex object
|
||||
- Not a list of IDs or strings
|
||||
- Not natural language text
|
||||
- UNLESS the answer can be straightforwardly verified using DIRECT STRING COMPARISON
|
||||
- And can be realistically reproduced
|
||||
- It should be unlikely that an LLM would return the same list in any other order or format
|
||||
|
||||
## Evaluation Process
|
||||
|
||||
### Step 1: Documentation Inspection
|
||||
|
||||
Read the documentation of the target API to understand:
|
||||
- Available endpoints and functionality
|
||||
- If ambiguity exists, fetch additional information from the web
|
||||
- Parallelize this step AS MUCH AS POSSIBLE
|
||||
- Ensure each subagent is ONLY examining documentation from the file system or on the web
|
||||
|
||||
### Step 2: Tool Inspection
|
||||
|
||||
List the tools available in the MCP server:
|
||||
- Inspect the MCP server directly
|
||||
- Understand input/output schemas, docstrings, and descriptions
|
||||
- WITHOUT calling the tools themselves at this stage
|
||||
|
||||
### Step 3: Developing Understanding
|
||||
|
||||
Repeat steps 1 & 2 until you have a good understanding:
|
||||
- Iterate multiple times
|
||||
- Think about the kinds of tasks you want to create
|
||||
- Refine your understanding
|
||||
- At NO stage should you READ the code of the MCP server implementation itself
|
||||
- Use your intuition and understanding to create reasonable, realistic, but VERY challenging tasks
|
||||
|
||||
### Step 4: Read-Only Content Inspection
|
||||
|
||||
After understanding the API and tools, USE the MCP server tools:
|
||||
- Inspect content using READ-ONLY and NON-DESTRUCTIVE operations ONLY
|
||||
- Goal: identify specific content (e.g., users, channels, messages, projects, tasks) for creating realistic questions
|
||||
- Should NOT call any tools that modify state
|
||||
- Will NOT read the code of the MCP server implementation itself
|
||||
- Parallelize this step with individual sub-agents pursuing independent explorations
|
||||
- Ensure each subagent is only performing READ-ONLY, NON-DESTRUCTIVE, and IDEMPOTENT operations
|
||||
- BE CAREFUL: SOME TOOLS may return LOTS OF DATA which would cause you to run out of CONTEXT
|
||||
- Make INCREMENTAL, SMALL, AND TARGETED tool calls for exploration
|
||||
- In all tool call requests, use the `limit` parameter to limit results (<10)
|
||||
- Use pagination
|
||||
|
||||
### Step 5: Task Generation
|
||||
|
||||
After inspecting the content, create 10 human-readable questions:
|
||||
- An LLM should be able to answer these with the MCP server
|
||||
- Follow all question and answer guidelines above
|
||||
|
||||
## Output Format
|
||||
|
||||
Each QA pair consists of a question and an answer. The output should be an XML file with this structure:
|
||||
|
||||
```xml
|
||||
<evaluation>
|
||||
<qa_pair>
|
||||
<question>Find the project created in Q2 2024 with the highest number of completed tasks. What is the project name?</question>
|
||||
<answer>Website Redesign</answer>
|
||||
</qa_pair>
|
||||
<qa_pair>
|
||||
<question>Search for issues labeled as "bug" that were closed in March 2024. Which user closed the most issues? Provide their username.</question>
|
||||
<answer>sarah_dev</answer>
|
||||
</qa_pair>
|
||||
<qa_pair>
|
||||
<question>Look for pull requests that modified files in the /api directory and were merged between January 1 and January 31, 2024. How many different contributors worked on these PRs?</question>
|
||||
<answer>7</answer>
|
||||
</qa_pair>
|
||||
<qa_pair>
|
||||
<question>Find the repository with the most stars that was created before 2023. What is the repository name?</question>
|
||||
<answer>data-pipeline</answer>
|
||||
</qa_pair>
|
||||
</evaluation>
|
||||
```
|
||||
|
||||
## Evaluation Examples
|
||||
|
||||
### Good Questions
|
||||
|
||||
**Example 1: Multi-hop question requiring deep exploration (GitHub MCP)**
|
||||
```xml
|
||||
<qa_pair>
|
||||
<question>Find the repository that was archived in Q3 2023 and had previously been the most forked project in the organization. What was the primary programming language used in that repository?</question>
|
||||
<answer>Python</answer>
|
||||
</qa_pair>
|
||||
```
|
||||
|
||||
This question is good because:
|
||||
- Requires multiple searches to find archived repositories
|
||||
- Needs to identify which had the most forks before archival
|
||||
- Requires examining repository details for the language
|
||||
- Answer is a simple, verifiable value
|
||||
- Based on historical (closed) data that won't change
|
||||
|
||||
**Example 2: Requires understanding context without keyword matching (Project Management MCP)**
|
||||
```xml
|
||||
<qa_pair>
|
||||
<question>Locate the initiative focused on improving customer onboarding that was completed in late 2023. The project lead created a retrospective document after completion. What was the lead's role title at that time?</question>
|
||||
<answer>Product Manager</answer>
|
||||
</qa_pair>
|
||||
```
|
||||
|
||||
This question is good because:
|
||||
- Doesn't use specific project name ("initiative focused on improving customer onboarding")
|
||||
- Requires finding completed projects from specific timeframe
|
||||
- Needs to identify the project lead and their role
|
||||
- Requires understanding context from retrospective documents
|
||||
- Answer is human-readable and stable
|
||||
- Based on completed work (won't change)
|
||||
|
||||
**Example 3: Complex aggregation requiring multiple steps (Issue Tracker MCP)**
|
||||
```xml
|
||||
<qa_pair>
|
||||
<question>Among all bugs reported in January 2024 that were marked as critical priority, which assignee resolved the highest percentage of their assigned bugs within 48 hours? Provide the assignee's username.</question>
|
||||
<answer>alex_eng</answer>
|
||||
</qa_pair>
|
||||
```
|
||||
|
||||
This question is good because:
|
||||
- Requires filtering bugs by date, priority, and status
|
||||
- Needs to group by assignee and calculate resolution rates
|
||||
- Requires understanding timestamps to determine 48-hour windows
|
||||
- Tests pagination (potentially many bugs to process)
|
||||
- Answer is a single username
|
||||
- Based on historical data from specific time period
|
||||
|
||||
**Example 4: Requires synthesis across multiple data types (CRM MCP)**
|
||||
```xml
|
||||
<qa_pair>
|
||||
<question>Find the account that upgraded from the Starter to Enterprise plan in Q4 2023 and had the highest annual contract value. What industry does this account operate in?</question>
|
||||
<answer>Healthcare</answer>
|
||||
</qa_pair>
|
||||
```
|
||||
|
||||
This question is good because:
|
||||
- Requires understanding subscription tier changes
|
||||
- Needs to identify upgrade events in specific timeframe
|
||||
- Requires comparing contract values
|
||||
- Must access account industry information
|
||||
- Answer is simple and verifiable
|
||||
- Based on completed historical transactions
|
||||
|
||||
### Poor Questions
|
||||
|
||||
**Example 1: Answer changes over time**
|
||||
```xml
|
||||
<qa_pair>
|
||||
<question>How many open issues are currently assigned to the engineering team?</question>
|
||||
<answer>47</answer>
|
||||
</qa_pair>
|
||||
```
|
||||
|
||||
This question is poor because:
|
||||
- The answer will change as issues are created, closed, or reassigned
|
||||
- Not based on stable/stationary data
|
||||
- Relies on "current state" which is dynamic
|
||||
|
||||
**Example 2: Too easy with keyword search**
|
||||
```xml
|
||||
<qa_pair>
|
||||
<question>Find the pull request with title "Add authentication feature" and tell me who created it.</question>
|
||||
<answer>developer123</answer>
|
||||
</qa_pair>
|
||||
```
|
||||
|
||||
This question is poor because:
|
||||
- Can be solved with a straightforward keyword search for exact title
|
||||
- Doesn't require deep exploration or understanding
|
||||
- No synthesis or analysis needed
|
||||
|
||||
**Example 3: Ambiguous answer format**
|
||||
```xml
|
||||
<qa_pair>
|
||||
<question>List all the repositories that have Python as their primary language.</question>
|
||||
<answer>repo1, repo2, repo3, data-pipeline, ml-tools</answer>
|
||||
</qa_pair>
|
||||
```
|
||||
|
||||
This question is poor because:
|
||||
- Answer is a list that could be returned in any order
|
||||
- Difficult to verify with direct string comparison
|
||||
- LLM might format differently (JSON array, comma-separated, newline-separated)
|
||||
- Better to ask for a specific aggregate (count) or superlative (most stars)
|
||||
|
||||
## Verification Process
|
||||
|
||||
After creating evaluations:
|
||||
|
||||
1. **Examine the XML file** to understand the schema
|
||||
2. **Load each task instruction** and in parallel using the MCP server and tools, identify the correct answer by attempting to solve the task YOURSELF
|
||||
3. **Flag any operations** that require WRITE or DESTRUCTIVE operations
|
||||
4. **Accumulate all CORRECT answers** and replace any incorrect answers in the document
|
||||
5. **Remove any `<qa_pair>`** that require WRITE or DESTRUCTIVE operations
|
||||
|
||||
Remember to parallelize solving tasks to avoid running out of context, then accumulate all answers and make changes to the file at the end.
|
||||
|
||||
## Tips for Creating Quality Evaluations
|
||||
|
||||
1. **Think Hard and Plan Ahead** before generating tasks
|
||||
2. **Parallelize Where Opportunity Arises** to speed up the process and manage context
|
||||
3. **Focus on Realistic Use Cases** that humans would actually want to accomplish
|
||||
4. **Create Challenging Questions** that test the limits of the MCP server's capabilities
|
||||
5. **Ensure Stability** by using historical data and closed concepts
|
||||
6. **Verify Answers** by solving the questions yourself using the MCP server tools
|
||||
7. **Iterate and Refine** based on what you learn during the process
|
||||
|
||||
---
|
||||
|
||||
# Running Evaluations
|
||||
|
||||
After creating your evaluation file, you can use the provided evaluation harness to test your MCP server.
|
||||
|
||||
## Setup
|
||||
|
||||
1. **Install Dependencies**
|
||||
|
||||
```bash
|
||||
pip install -r scripts/requirements.txt
|
||||
```
|
||||
|
||||
Or install manually:
|
||||
```bash
|
||||
pip install anthropic mcp
|
||||
```
|
||||
|
||||
2. **Set API Key**
|
||||
|
||||
```bash
|
||||
export ANTHROPIC_API_KEY=your_api_key_here
|
||||
```
|
||||
|
||||
## Evaluation File Format
|
||||
|
||||
Evaluation files use XML format with `<qa_pair>` elements:
|
||||
|
||||
```xml
|
||||
<evaluation>
|
||||
<qa_pair>
|
||||
<question>Find the project created in Q2 2024 with the highest number of completed tasks. What is the project name?</question>
|
||||
<answer>Website Redesign</answer>
|
||||
</qa_pair>
|
||||
<qa_pair>
|
||||
<question>Search for issues labeled as "bug" that were closed in March 2024. Which user closed the most issues? Provide their username.</question>
|
||||
<answer>sarah_dev</answer>
|
||||
</qa_pair>
|
||||
</evaluation>
|
||||
```
|
||||
|
||||
## Running Evaluations
|
||||
|
||||
The evaluation script (`scripts/evaluation.py`) supports three transport types:
|
||||
|
||||
**Important:**
|
||||
- **stdio transport**: The evaluation script automatically launches and manages the MCP server process for you. Do not run the server manually.
|
||||
- **sse/http transports**: You must start the MCP server separately before running the evaluation. The script connects to the already-running server at the specified URL.
|
||||
|
||||
### 1. Local STDIO Server
|
||||
|
||||
For locally-run MCP servers (script launches the server automatically):
|
||||
|
||||
```bash
|
||||
python scripts/evaluation.py \
|
||||
-t stdio \
|
||||
-c python \
|
||||
-a my_mcp_server.py \
|
||||
evaluation.xml
|
||||
```
|
||||
|
||||
With environment variables:
|
||||
```bash
|
||||
python scripts/evaluation.py \
|
||||
-t stdio \
|
||||
-c python \
|
||||
-a my_mcp_server.py \
|
||||
-e API_KEY=abc123 \
|
||||
-e DEBUG=true \
|
||||
evaluation.xml
|
||||
```
|
||||
|
||||
### 2. Server-Sent Events (SSE)
|
||||
|
||||
For SSE-based MCP servers (you must start the server first):
|
||||
|
||||
```bash
|
||||
python scripts/evaluation.py \
|
||||
-t sse \
|
||||
-u https://example.com/mcp \
|
||||
-H "Authorization: Bearer token123" \
|
||||
-H "X-Custom-Header: value" \
|
||||
evaluation.xml
|
||||
```
|
||||
|
||||
### 3. HTTP (Streamable HTTP)
|
||||
|
||||
For HTTP-based MCP servers (you must start the server first):
|
||||
|
||||
```bash
|
||||
python scripts/evaluation.py \
|
||||
-t http \
|
||||
-u https://example.com/mcp \
|
||||
-H "Authorization: Bearer token123" \
|
||||
evaluation.xml
|
||||
```
|
||||
|
||||
## Command-Line Options
|
||||
|
||||
```
|
||||
usage: evaluation.py [-h] [-t {stdio,sse,http}] [-m MODEL] [-c COMMAND]
|
||||
[-a ARGS [ARGS ...]] [-e ENV [ENV ...]] [-u URL]
|
||||
[-H HEADERS [HEADERS ...]] [-o OUTPUT]
|
||||
eval_file
|
||||
|
||||
positional arguments:
|
||||
eval_file Path to evaluation XML file
|
||||
|
||||
optional arguments:
|
||||
-h, --help Show help message
|
||||
-t, --transport Transport type: stdio, sse, or http (default: stdio)
|
||||
-m, --model Claude model to use (default: claude-3-7-sonnet-20250219)
|
||||
-o, --output Output file for report (default: print to stdout)
|
||||
|
||||
stdio options:
|
||||
-c, --command Command to run MCP server (e.g., python, node)
|
||||
-a, --args Arguments for the command (e.g., server.py)
|
||||
-e, --env Environment variables in KEY=VALUE format
|
||||
|
||||
sse/http options:
|
||||
-u, --url MCP server URL
|
||||
-H, --header HTTP headers in 'Key: Value' format
|
||||
```
|
||||
|
||||
## Output
|
||||
|
||||
The evaluation script generates a detailed report including:
|
||||
|
||||
- **Summary Statistics**:
|
||||
- Accuracy (correct/total)
|
||||
- Average task duration
|
||||
- Average tool calls per task
|
||||
- Total tool calls
|
||||
|
||||
- **Per-Task Results**:
|
||||
- Prompt and expected response
|
||||
- Actual response from the agent
|
||||
- Whether the answer was correct (✅/❌)
|
||||
- Duration and tool call details
|
||||
- Agent's summary of its approach
|
||||
- Agent's feedback on the tools
|
||||
|
||||
### Save Report to File
|
||||
|
||||
```bash
|
||||
python scripts/evaluation.py \
|
||||
-t stdio \
|
||||
-c python \
|
||||
-a my_server.py \
|
||||
-o evaluation_report.md \
|
||||
evaluation.xml
|
||||
```
|
||||
|
||||
## Complete Example Workflow
|
||||
|
||||
Here's a complete example of creating and running an evaluation:
|
||||
|
||||
1. **Create your evaluation file** (`my_evaluation.xml`):
|
||||
|
||||
```xml
|
||||
<evaluation>
|
||||
<qa_pair>
|
||||
<question>Find the user who created the most issues in January 2024. What is their username?</question>
|
||||
<answer>alice_developer</answer>
|
||||
</qa_pair>
|
||||
<qa_pair>
|
||||
<question>Among all pull requests merged in Q1 2024, which repository had the highest number? Provide the repository name.</question>
|
||||
<answer>backend-api</answer>
|
||||
</qa_pair>
|
||||
<qa_pair>
|
||||
<question>Find the project that was completed in December 2023 and had the longest duration from start to finish. How many days did it take?</question>
|
||||
<answer>127</answer>
|
||||
</qa_pair>
|
||||
</evaluation>
|
||||
```
|
||||
|
||||
2. **Install dependencies**:
|
||||
|
||||
```bash
|
||||
pip install -r scripts/requirements.txt
|
||||
export ANTHROPIC_API_KEY=your_api_key
|
||||
```
|
||||
|
||||
3. **Run evaluation**:
|
||||
|
||||
```bash
|
||||
python scripts/evaluation.py \
|
||||
-t stdio \
|
||||
-c python \
|
||||
-a github_mcp_server.py \
|
||||
-e GITHUB_TOKEN=ghp_xxx \
|
||||
-o github_eval_report.md \
|
||||
my_evaluation.xml
|
||||
```
|
||||
|
||||
4. **Review the report** in `github_eval_report.md` to:
|
||||
- See which questions passed/failed
|
||||
- Read the agent's feedback on your tools
|
||||
- Identify areas for improvement
|
||||
- Iterate on your MCP server design
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
### Connection Errors
|
||||
|
||||
If you get connection errors:
|
||||
- **STDIO**: Verify the command and arguments are correct
|
||||
- **SSE/HTTP**: Check the URL is accessible and headers are correct
|
||||
- Ensure any required API keys are set in environment variables or headers
|
||||
|
||||
### Low Accuracy
|
||||
|
||||
If many evaluations fail:
|
||||
- Review the agent's feedback for each task
|
||||
- Check if tool descriptions are clear and comprehensive
|
||||
- Verify input parameters are well-documented
|
||||
- Consider whether tools return too much or too little data
|
||||
- Ensure error messages are actionable
|
||||
|
||||
### Timeout Issues
|
||||
|
||||
If tasks are timing out:
|
||||
- Use a more capable model (e.g., `claude-3-7-sonnet-20250219`)
|
||||
- Check if tools are returning too much data
|
||||
- Verify pagination is working correctly
|
||||
- Consider simplifying complex questions
|
||||
@@ -0,0 +1,249 @@
|
||||
# MCP Server Best Practices
|
||||
|
||||
## Quick Reference
|
||||
|
||||
### Server Naming
|
||||
- **Python**: `{service}_mcp` (e.g., `slack_mcp`)
|
||||
- **Node/TypeScript**: `{service}-mcp-server` (e.g., `slack-mcp-server`)
|
||||
|
||||
### Tool Naming
|
||||
- Use snake_case with service prefix
|
||||
- Format: `{service}_{action}_{resource}`
|
||||
- Example: `slack_send_message`, `github_create_issue`
|
||||
|
||||
### Response Formats
|
||||
- Support both JSON and Markdown formats
|
||||
- JSON for programmatic processing
|
||||
- Markdown for human readability
|
||||
|
||||
### Pagination
|
||||
- Always respect `limit` parameter
|
||||
- Return `has_more`, `next_offset`, `total_count`
|
||||
- Default to 20-50 items
|
||||
|
||||
### Transport
|
||||
- **Streamable HTTP**: For remote servers, multi-client scenarios
|
||||
- **stdio**: For local integrations, command-line tools
|
||||
- Avoid SSE (deprecated in favor of streamable HTTP)
|
||||
|
||||
---
|
||||
|
||||
## Server Naming Conventions
|
||||
|
||||
Follow these standardized naming patterns:
|
||||
|
||||
**Python**: Use format `{service}_mcp` (lowercase with underscores)
|
||||
- Examples: `slack_mcp`, `github_mcp`, `jira_mcp`
|
||||
|
||||
**Node/TypeScript**: Use format `{service}-mcp-server` (lowercase with hyphens)
|
||||
- Examples: `slack-mcp-server`, `github-mcp-server`, `jira-mcp-server`
|
||||
|
||||
The name should be general, descriptive of the service being integrated, easy to infer from the task description, and without version numbers.
|
||||
|
||||
---
|
||||
|
||||
## Tool Naming and Design
|
||||
|
||||
### Tool Naming
|
||||
|
||||
1. **Use snake_case**: `search_users`, `create_project`, `get_channel_info`
|
||||
2. **Include service prefix**: Anticipate that your MCP server may be used alongside other MCP servers
|
||||
- Use `slack_send_message` instead of just `send_message`
|
||||
- Use `github_create_issue` instead of just `create_issue`
|
||||
3. **Be action-oriented**: Start with verbs (get, list, search, create, etc.)
|
||||
4. **Be specific**: Avoid generic names that could conflict with other servers
|
||||
|
||||
### Tool Design
|
||||
|
||||
- Tool descriptions must narrowly and unambiguously describe functionality
|
||||
- Descriptions must precisely match actual functionality
|
||||
- Provide tool annotations (readOnlyHint, destructiveHint, idempotentHint, openWorldHint)
|
||||
- Keep tool operations focused and atomic
|
||||
|
||||
---
|
||||
|
||||
## Response Formats
|
||||
|
||||
All tools that return data should support multiple formats:
|
||||
|
||||
### JSON Format (`response_format="json"`)
|
||||
- Machine-readable structured data
|
||||
- Include all available fields and metadata
|
||||
- Consistent field names and types
|
||||
- Use for programmatic processing
|
||||
|
||||
### Markdown Format (`response_format="markdown"`, typically default)
|
||||
- Human-readable formatted text
|
||||
- Use headers, lists, and formatting for clarity
|
||||
- Convert timestamps to human-readable format
|
||||
- Show display names with IDs in parentheses
|
||||
- Omit verbose metadata
|
||||
|
||||
---
|
||||
|
||||
## Pagination
|
||||
|
||||
For tools that list resources:
|
||||
|
||||
- **Always respect the `limit` parameter**
|
||||
- **Implement pagination**: Use `offset` or cursor-based pagination
|
||||
- **Return pagination metadata**: Include `has_more`, `next_offset`/`next_cursor`, `total_count`
|
||||
- **Never load all results into memory**: Especially important for large datasets
|
||||
- **Default to reasonable limits**: 20-50 items is typical
|
||||
|
||||
Example pagination response:
|
||||
```json
|
||||
{
|
||||
"total": 150,
|
||||
"count": 20,
|
||||
"offset": 0,
|
||||
"items": [...],
|
||||
"has_more": true,
|
||||
"next_offset": 20
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Transport Options
|
||||
|
||||
### Streamable HTTP
|
||||
|
||||
**Best for**: Remote servers, web services, multi-client scenarios
|
||||
|
||||
**Characteristics**:
|
||||
- Bidirectional communication over HTTP
|
||||
- Supports multiple simultaneous clients
|
||||
- Can be deployed as a web service
|
||||
- Enables server-to-client notifications
|
||||
|
||||
**Use when**:
|
||||
- Serving multiple clients simultaneously
|
||||
- Deploying as a cloud service
|
||||
- Integration with web applications
|
||||
|
||||
### stdio
|
||||
|
||||
**Best for**: Local integrations, command-line tools
|
||||
|
||||
**Characteristics**:
|
||||
- Standard input/output stream communication
|
||||
- Simple setup, no network configuration needed
|
||||
- Runs as a subprocess of the client
|
||||
|
||||
**Use when**:
|
||||
- Building tools for local development environments
|
||||
- Integrating with desktop applications
|
||||
- Single-user, single-session scenarios
|
||||
|
||||
**Note**: stdio servers should NOT log to stdout (use stderr for logging)
|
||||
|
||||
### Transport Selection
|
||||
|
||||
| Criterion | stdio | Streamable HTTP |
|
||||
|-----------|-------|-----------------|
|
||||
| **Deployment** | Local | Remote |
|
||||
| **Clients** | Single | Multiple |
|
||||
| **Complexity** | Low | Medium |
|
||||
| **Real-time** | No | Yes |
|
||||
|
||||
---
|
||||
|
||||
## Security Best Practices
|
||||
|
||||
### Authentication and Authorization
|
||||
|
||||
**OAuth 2.1**:
|
||||
- Use secure OAuth 2.1 with certificates from recognized authorities
|
||||
- Validate access tokens before processing requests
|
||||
- Only accept tokens specifically intended for your server
|
||||
|
||||
**API Keys**:
|
||||
- Store API keys in environment variables, never in code
|
||||
- Validate keys on server startup
|
||||
- Provide clear error messages when authentication fails
|
||||
|
||||
### Input Validation
|
||||
|
||||
- Sanitize file paths to prevent directory traversal
|
||||
- Validate URLs and external identifiers
|
||||
- Check parameter sizes and ranges
|
||||
- Prevent command injection in system calls
|
||||
- Use schema validation (Pydantic/Zod) for all inputs
|
||||
|
||||
### Error Handling
|
||||
|
||||
- Don't expose internal errors to clients
|
||||
- Log security-relevant errors server-side
|
||||
- Provide helpful but not revealing error messages
|
||||
- Clean up resources after errors
|
||||
|
||||
### DNS Rebinding Protection
|
||||
|
||||
For streamable HTTP servers running locally:
|
||||
- Enable DNS rebinding protection
|
||||
- Validate the `Origin` header on all incoming connections
|
||||
- Bind to `127.0.0.1` rather than `0.0.0.0`
|
||||
|
||||
---
|
||||
|
||||
## Tool Annotations
|
||||
|
||||
Provide annotations to help clients understand tool behavior:
|
||||
|
||||
| Annotation | Type | Default | Description |
|
||||
|-----------|------|---------|-------------|
|
||||
| `readOnlyHint` | boolean | false | Tool does not modify its environment |
|
||||
| `destructiveHint` | boolean | true | Tool may perform destructive updates |
|
||||
| `idempotentHint` | boolean | false | Repeated calls with same args have no additional effect |
|
||||
| `openWorldHint` | boolean | true | Tool interacts with external entities |
|
||||
|
||||
**Important**: Annotations are hints, not security guarantees. Clients should not make security-critical decisions based solely on annotations.
|
||||
|
||||
---
|
||||
|
||||
## Error Handling
|
||||
|
||||
- Use standard JSON-RPC error codes
|
||||
- Report tool errors within result objects (not protocol-level errors)
|
||||
- Provide helpful, specific error messages with suggested next steps
|
||||
- Don't expose internal implementation details
|
||||
- Clean up resources properly on errors
|
||||
|
||||
Example error handling:
|
||||
```typescript
|
||||
try {
|
||||
const result = performOperation();
|
||||
return { content: [{ type: "text", text: result }] };
|
||||
} catch (error) {
|
||||
return {
|
||||
isError: true,
|
||||
content: [{
|
||||
type: "text",
|
||||
text: `Error: ${error.message}. Try using filter='active_only' to reduce results.`
|
||||
}]
|
||||
};
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Testing Requirements
|
||||
|
||||
Comprehensive testing should cover:
|
||||
|
||||
- **Functional testing**: Verify correct execution with valid/invalid inputs
|
||||
- **Integration testing**: Test interaction with external systems
|
||||
- **Security testing**: Validate auth, input sanitization, rate limiting
|
||||
- **Performance testing**: Check behavior under load, timeouts
|
||||
- **Error handling**: Ensure proper error reporting and cleanup
|
||||
|
||||
---
|
||||
|
||||
## Documentation Requirements
|
||||
|
||||
- Provide clear documentation of all tools and capabilities
|
||||
- Include working examples (at least 3 per major feature)
|
||||
- Document security considerations
|
||||
- Specify required permissions and access levels
|
||||
- Document rate limits and performance characteristics
|
||||
@@ -0,0 +1,970 @@
|
||||
# Node/TypeScript MCP Server Implementation Guide
|
||||
|
||||
## Overview
|
||||
|
||||
This document provides Node/TypeScript-specific best practices and examples for implementing MCP servers using the MCP TypeScript SDK. It covers project structure, server setup, tool registration patterns, input validation with Zod, error handling, and complete working examples.
|
||||
|
||||
---
|
||||
|
||||
## Quick Reference
|
||||
|
||||
### Key Imports
|
||||
```typescript
|
||||
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
|
||||
import { StreamableHTTPServerTransport } from "@modelcontextprotocol/sdk/server/streamableHttp.js";
|
||||
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
|
||||
import express from "express";
|
||||
import { z } from "zod";
|
||||
```
|
||||
|
||||
### Server Initialization
|
||||
```typescript
|
||||
const server = new McpServer({
|
||||
name: "service-mcp-server",
|
||||
version: "1.0.0"
|
||||
});
|
||||
```
|
||||
|
||||
### Tool Registration Pattern
|
||||
```typescript
|
||||
server.registerTool(
|
||||
"tool_name",
|
||||
{
|
||||
title: "Tool Display Name",
|
||||
description: "What the tool does",
|
||||
inputSchema: { param: z.string() },
|
||||
outputSchema: { result: z.string() }
|
||||
},
|
||||
async ({ param }) => {
|
||||
const output = { result: `Processed: ${param}` };
|
||||
return {
|
||||
content: [{ type: "text", text: JSON.stringify(output) }],
|
||||
structuredContent: output // Modern pattern for structured data
|
||||
};
|
||||
}
|
||||
);
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## MCP TypeScript SDK
|
||||
|
||||
The official MCP TypeScript SDK provides:
|
||||
- `McpServer` class for server initialization
|
||||
- `registerTool` method for tool registration
|
||||
- Zod schema integration for runtime input validation
|
||||
- Type-safe tool handler implementations
|
||||
|
||||
**IMPORTANT - Use Modern APIs Only:**
|
||||
- **DO use**: `server.registerTool()`, `server.registerResource()`, `server.registerPrompt()`
|
||||
- **DO NOT use**: Old deprecated APIs such as `server.tool()`, `server.setRequestHandler(ListToolsRequestSchema, ...)`, or manual handler registration
|
||||
- The `register*` methods provide better type safety, automatic schema handling, and are the recommended approach
|
||||
|
||||
See the MCP SDK documentation in the references for complete details.
|
||||
|
||||
## Server Naming Convention
|
||||
|
||||
Node/TypeScript MCP servers must follow this naming pattern:
|
||||
- **Format**: `{service}-mcp-server` (lowercase with hyphens)
|
||||
- **Examples**: `github-mcp-server`, `jira-mcp-server`, `stripe-mcp-server`
|
||||
|
||||
The name should be:
|
||||
- General (not tied to specific features)
|
||||
- Descriptive of the service/API being integrated
|
||||
- Easy to infer from the task description
|
||||
- Without version numbers or dates
|
||||
|
||||
## Project Structure
|
||||
|
||||
Create the following structure for Node/TypeScript MCP servers:
|
||||
|
||||
```
|
||||
{service}-mcp-server/
|
||||
├── package.json
|
||||
├── tsconfig.json
|
||||
├── README.md
|
||||
├── src/
|
||||
│ ├── index.ts # Main entry point with McpServer initialization
|
||||
│ ├── types.ts # TypeScript type definitions and interfaces
|
||||
│ ├── tools/ # Tool implementations (one file per domain)
|
||||
│ ├── services/ # API clients and shared utilities
|
||||
│ ├── schemas/ # Zod validation schemas
|
||||
│ └── constants.ts # Shared constants (API_URL, CHARACTER_LIMIT, etc.)
|
||||
└── dist/ # Built JavaScript files (entry point: dist/index.js)
|
||||
```
|
||||
|
||||
## Tool Implementation
|
||||
|
||||
### Tool Naming
|
||||
|
||||
Use snake_case for tool names (e.g., "search_users", "create_project", "get_channel_info") with clear, action-oriented names.
|
||||
|
||||
**Avoid Naming Conflicts**: Include the service context to prevent overlaps:
|
||||
- Use "slack_send_message" instead of just "send_message"
|
||||
- Use "github_create_issue" instead of just "create_issue"
|
||||
- Use "asana_list_tasks" instead of just "list_tasks"
|
||||
|
||||
### Tool Structure
|
||||
|
||||
Tools are registered using the `registerTool` method with the following requirements:
|
||||
- Use Zod schemas for runtime input validation and type safety
|
||||
- The `description` field must be explicitly provided - JSDoc comments are NOT automatically extracted
|
||||
- Explicitly provide `title`, `description`, `inputSchema`, and `annotations`
|
||||
- The `inputSchema` must be a Zod schema object (not a JSON schema)
|
||||
- Type all parameters and return values explicitly
|
||||
|
||||
```typescript
|
||||
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
|
||||
import { z } from "zod";
|
||||
|
||||
const server = new McpServer({
|
||||
name: "example-mcp",
|
||||
version: "1.0.0"
|
||||
});
|
||||
|
||||
// Zod schema for input validation
|
||||
const UserSearchInputSchema = z.object({
|
||||
query: z.string()
|
||||
.min(2, "Query must be at least 2 characters")
|
||||
.max(200, "Query must not exceed 200 characters")
|
||||
.describe("Search string to match against names/emails"),
|
||||
limit: z.number()
|
||||
.int()
|
||||
.min(1)
|
||||
.max(100)
|
||||
.default(20)
|
||||
.describe("Maximum results to return"),
|
||||
offset: z.number()
|
||||
.int()
|
||||
.min(0)
|
||||
.default(0)
|
||||
.describe("Number of results to skip for pagination"),
|
||||
response_format: z.nativeEnum(ResponseFormat)
|
||||
.default(ResponseFormat.MARKDOWN)
|
||||
.describe("Output format: 'markdown' for human-readable or 'json' for machine-readable")
|
||||
}).strict();
|
||||
|
||||
// Type definition from Zod schema
|
||||
type UserSearchInput = z.infer<typeof UserSearchInputSchema>;
|
||||
|
||||
server.registerTool(
|
||||
"example_search_users",
|
||||
{
|
||||
title: "Search Example Users",
|
||||
description: `Search for users in the Example system by name, email, or team.
|
||||
|
||||
This tool searches across all user profiles in the Example platform, supporting partial matches and various search filters. It does NOT create or modify users, only searches existing ones.
|
||||
|
||||
Args:
|
||||
- query (string): Search string to match against names/emails
|
||||
- limit (number): Maximum results to return, between 1-100 (default: 20)
|
||||
- offset (number): Number of results to skip for pagination (default: 0)
|
||||
- response_format ('markdown' | 'json'): Output format (default: 'markdown')
|
||||
|
||||
Returns:
|
||||
For JSON format: Structured data with schema:
|
||||
{
|
||||
"total": number, // Total number of matches found
|
||||
"count": number, // Number of results in this response
|
||||
"offset": number, // Current pagination offset
|
||||
"users": [
|
||||
{
|
||||
"id": string, // User ID (e.g., "U123456789")
|
||||
"name": string, // Full name (e.g., "John Doe")
|
||||
"email": string, // Email address
|
||||
"team": string, // Team name (optional)
|
||||
"active": boolean // Whether user is active
|
||||
}
|
||||
],
|
||||
"has_more": boolean, // Whether more results are available
|
||||
"next_offset": number // Offset for next page (if has_more is true)
|
||||
}
|
||||
|
||||
Examples:
|
||||
- Use when: "Find all marketing team members" -> params with query="team:marketing"
|
||||
- Use when: "Search for John's account" -> params with query="john"
|
||||
- Don't use when: You need to create a user (use example_create_user instead)
|
||||
|
||||
Error Handling:
|
||||
- Returns "Error: Rate limit exceeded" if too many requests (429 status)
|
||||
- Returns "No users found matching '<query>'" if search returns empty`,
|
||||
inputSchema: UserSearchInputSchema,
|
||||
annotations: {
|
||||
readOnlyHint: true,
|
||||
destructiveHint: false,
|
||||
idempotentHint: true,
|
||||
openWorldHint: true
|
||||
}
|
||||
},
|
||||
async (params: UserSearchInput) => {
|
||||
try {
|
||||
// Input validation is handled by Zod schema
|
||||
// Make API request using validated parameters
|
||||
const data = await makeApiRequest<any>(
|
||||
"users/search",
|
||||
"GET",
|
||||
undefined,
|
||||
{
|
||||
q: params.query,
|
||||
limit: params.limit,
|
||||
offset: params.offset
|
||||
}
|
||||
);
|
||||
|
||||
const users = data.users || [];
|
||||
const total = data.total || 0;
|
||||
|
||||
if (!users.length) {
|
||||
return {
|
||||
content: [{
|
||||
type: "text",
|
||||
text: `No users found matching '${params.query}'`
|
||||
}]
|
||||
};
|
||||
}
|
||||
|
||||
// Prepare structured output
|
||||
const output = {
|
||||
total,
|
||||
count: users.length,
|
||||
offset: params.offset,
|
||||
users: users.map((user: any) => ({
|
||||
id: user.id,
|
||||
name: user.name,
|
||||
email: user.email,
|
||||
...(user.team ? { team: user.team } : {}),
|
||||
active: user.active ?? true
|
||||
})),
|
||||
has_more: total > params.offset + users.length,
|
||||
...(total > params.offset + users.length ? {
|
||||
next_offset: params.offset + users.length
|
||||
} : {})
|
||||
};
|
||||
|
||||
// Format text representation based on requested format
|
||||
let textContent: string;
|
||||
if (params.response_format === ResponseFormat.MARKDOWN) {
|
||||
const lines = [`# User Search Results: '${params.query}'`, "",
|
||||
`Found ${total} users (showing ${users.length})`, ""];
|
||||
for (const user of users) {
|
||||
lines.push(`## ${user.name} (${user.id})`);
|
||||
lines.push(`- **Email**: ${user.email}`);
|
||||
if (user.team) lines.push(`- **Team**: ${user.team}`);
|
||||
lines.push("");
|
||||
}
|
||||
textContent = lines.join("\n");
|
||||
} else {
|
||||
textContent = JSON.stringify(output, null, 2);
|
||||
}
|
||||
|
||||
return {
|
||||
content: [{ type: "text", text: textContent }],
|
||||
structuredContent: output // Modern pattern for structured data
|
||||
};
|
||||
} catch (error) {
|
||||
return {
|
||||
content: [{
|
||||
type: "text",
|
||||
text: handleApiError(error)
|
||||
}]
|
||||
};
|
||||
}
|
||||
}
|
||||
);
|
||||
```
|
||||
|
||||
## Zod Schemas for Input Validation
|
||||
|
||||
Zod provides runtime type validation:
|
||||
|
||||
```typescript
|
||||
import { z } from "zod";
|
||||
|
||||
// Basic schema with validation
|
||||
const CreateUserSchema = z.object({
|
||||
name: z.string()
|
||||
.min(1, "Name is required")
|
||||
.max(100, "Name must not exceed 100 characters"),
|
||||
email: z.string()
|
||||
.email("Invalid email format"),
|
||||
age: z.number()
|
||||
.int("Age must be a whole number")
|
||||
.min(0, "Age cannot be negative")
|
||||
.max(150, "Age cannot be greater than 150")
|
||||
}).strict(); // Use .strict() to forbid extra fields
|
||||
|
||||
// Enums
|
||||
enum ResponseFormat {
|
||||
MARKDOWN = "markdown",
|
||||
JSON = "json"
|
||||
}
|
||||
|
||||
const SearchSchema = z.object({
|
||||
response_format: z.nativeEnum(ResponseFormat)
|
||||
.default(ResponseFormat.MARKDOWN)
|
||||
.describe("Output format")
|
||||
});
|
||||
|
||||
// Optional fields with defaults
|
||||
const PaginationSchema = z.object({
|
||||
limit: z.number()
|
||||
.int()
|
||||
.min(1)
|
||||
.max(100)
|
||||
.default(20)
|
||||
.describe("Maximum results to return"),
|
||||
offset: z.number()
|
||||
.int()
|
||||
.min(0)
|
||||
.default(0)
|
||||
.describe("Number of results to skip")
|
||||
});
|
||||
```
|
||||
|
||||
## Response Format Options
|
||||
|
||||
Support multiple output formats for flexibility:
|
||||
|
||||
```typescript
|
||||
enum ResponseFormat {
|
||||
MARKDOWN = "markdown",
|
||||
JSON = "json"
|
||||
}
|
||||
|
||||
const inputSchema = z.object({
|
||||
query: z.string(),
|
||||
response_format: z.nativeEnum(ResponseFormat)
|
||||
.default(ResponseFormat.MARKDOWN)
|
||||
.describe("Output format: 'markdown' for human-readable or 'json' for machine-readable")
|
||||
});
|
||||
```
|
||||
|
||||
**Markdown format**:
|
||||
- Use headers, lists, and formatting for clarity
|
||||
- Convert timestamps to human-readable format
|
||||
- Show display names with IDs in parentheses
|
||||
- Omit verbose metadata
|
||||
- Group related information logically
|
||||
|
||||
**JSON format**:
|
||||
- Return complete, structured data suitable for programmatic processing
|
||||
- Include all available fields and metadata
|
||||
- Use consistent field names and types
|
||||
|
||||
## Pagination Implementation
|
||||
|
||||
For tools that list resources:
|
||||
|
||||
```typescript
|
||||
const ListSchema = z.object({
|
||||
limit: z.number().int().min(1).max(100).default(20),
|
||||
offset: z.number().int().min(0).default(0)
|
||||
});
|
||||
|
||||
async function listItems(params: z.infer<typeof ListSchema>) {
|
||||
const data = await apiRequest(params.limit, params.offset);
|
||||
|
||||
const response = {
|
||||
total: data.total,
|
||||
count: data.items.length,
|
||||
offset: params.offset,
|
||||
items: data.items,
|
||||
has_more: data.total > params.offset + data.items.length,
|
||||
next_offset: data.total > params.offset + data.items.length
|
||||
? params.offset + data.items.length
|
||||
: undefined
|
||||
};
|
||||
|
||||
return JSON.stringify(response, null, 2);
|
||||
}
|
||||
```
|
||||
|
||||
## Character Limits and Truncation
|
||||
|
||||
Add a CHARACTER_LIMIT constant to prevent overwhelming responses:
|
||||
|
||||
```typescript
|
||||
// At module level in constants.ts
|
||||
export const CHARACTER_LIMIT = 25000; // Maximum response size in characters
|
||||
|
||||
async function searchTool(params: SearchInput) {
|
||||
let result = generateResponse(data);
|
||||
|
||||
// Check character limit and truncate if needed
|
||||
if (result.length > CHARACTER_LIMIT) {
|
||||
const truncatedData = data.slice(0, Math.max(1, data.length / 2));
|
||||
response.data = truncatedData;
|
||||
response.truncated = true;
|
||||
response.truncation_message =
|
||||
`Response truncated from ${data.length} to ${truncatedData.length} items. ` +
|
||||
`Use 'offset' parameter or add filters to see more results.`;
|
||||
result = JSON.stringify(response, null, 2);
|
||||
}
|
||||
|
||||
return result;
|
||||
}
|
||||
```
|
||||
|
||||
## Error Handling
|
||||
|
||||
Provide clear, actionable error messages:
|
||||
|
||||
```typescript
|
||||
import axios, { AxiosError } from "axios";
|
||||
|
||||
function handleApiError(error: unknown): string {
|
||||
if (error instanceof AxiosError) {
|
||||
if (error.response) {
|
||||
switch (error.response.status) {
|
||||
case 404:
|
||||
return "Error: Resource not found. Please check the ID is correct.";
|
||||
case 403:
|
||||
return "Error: Permission denied. You don't have access to this resource.";
|
||||
case 429:
|
||||
return "Error: Rate limit exceeded. Please wait before making more requests.";
|
||||
default:
|
||||
return `Error: API request failed with status ${error.response.status}`;
|
||||
}
|
||||
} else if (error.code === "ECONNABORTED") {
|
||||
return "Error: Request timed out. Please try again.";
|
||||
}
|
||||
}
|
||||
return `Error: Unexpected error occurred: ${error instanceof Error ? error.message : String(error)}`;
|
||||
}
|
||||
```
|
||||
|
||||
## Shared Utilities
|
||||
|
||||
Extract common functionality into reusable functions:
|
||||
|
||||
```typescript
|
||||
// Shared API request function
|
||||
async function makeApiRequest<T>(
|
||||
endpoint: string,
|
||||
method: "GET" | "POST" | "PUT" | "DELETE" = "GET",
|
||||
data?: any,
|
||||
params?: any
|
||||
): Promise<T> {
|
||||
try {
|
||||
const response = await axios({
|
||||
method,
|
||||
url: `${API_BASE_URL}/${endpoint}`,
|
||||
data,
|
||||
params,
|
||||
timeout: 30000,
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
"Accept": "application/json"
|
||||
}
|
||||
});
|
||||
return response.data;
|
||||
} catch (error) {
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
## Async/Await Best Practices
|
||||
|
||||
Always use async/await for network requests and I/O operations:
|
||||
|
||||
```typescript
|
||||
// Good: Async network request
|
||||
async function fetchData(resourceId: string): Promise<ResourceData> {
|
||||
const response = await axios.get(`${API_URL}/resource/${resourceId}`);
|
||||
return response.data;
|
||||
}
|
||||
|
||||
// Bad: Promise chains
|
||||
function fetchData(resourceId: string): Promise<ResourceData> {
|
||||
return axios.get(`${API_URL}/resource/${resourceId}`)
|
||||
.then(response => response.data); // Harder to read and maintain
|
||||
}
|
||||
```
|
||||
|
||||
## TypeScript Best Practices
|
||||
|
||||
1. **Use Strict TypeScript**: Enable strict mode in tsconfig.json
|
||||
2. **Define Interfaces**: Create clear interface definitions for all data structures
|
||||
3. **Avoid `any`**: Use proper types or `unknown` instead of `any`
|
||||
4. **Zod for Runtime Validation**: Use Zod schemas to validate external data
|
||||
5. **Type Guards**: Create type guard functions for complex type checking
|
||||
6. **Error Handling**: Always use try-catch with proper error type checking
|
||||
7. **Null Safety**: Use optional chaining (`?.`) and nullish coalescing (`??`)
|
||||
|
||||
```typescript
|
||||
// Good: Type-safe with Zod and interfaces
|
||||
interface UserResponse {
|
||||
id: string;
|
||||
name: string;
|
||||
email: string;
|
||||
team?: string;
|
||||
active: boolean;
|
||||
}
|
||||
|
||||
const UserSchema = z.object({
|
||||
id: z.string(),
|
||||
name: z.string(),
|
||||
email: z.string().email(),
|
||||
team: z.string().optional(),
|
||||
active: z.boolean()
|
||||
});
|
||||
|
||||
type User = z.infer<typeof UserSchema>;
|
||||
|
||||
async function getUser(id: string): Promise<User> {
|
||||
const data = await apiCall(`/users/${id}`);
|
||||
return UserSchema.parse(data); // Runtime validation
|
||||
}
|
||||
|
||||
// Bad: Using any
|
||||
async function getUser(id: string): Promise<any> {
|
||||
return await apiCall(`/users/${id}`); // No type safety
|
||||
}
|
||||
```
|
||||
|
||||
## Package Configuration
|
||||
|
||||
### package.json
|
||||
|
||||
```json
|
||||
{
|
||||
"name": "{service}-mcp-server",
|
||||
"version": "1.0.0",
|
||||
"description": "MCP server for {Service} API integration",
|
||||
"type": "module",
|
||||
"main": "dist/index.js",
|
||||
"scripts": {
|
||||
"start": "node dist/index.js",
|
||||
"dev": "tsx watch src/index.ts",
|
||||
"build": "tsc",
|
||||
"clean": "rm -rf dist"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">=18"
|
||||
},
|
||||
"dependencies": {
|
||||
"@modelcontextprotocol/sdk": "^1.6.1",
|
||||
"axios": "^1.7.9",
|
||||
"zod": "^3.23.8"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@types/node": "^22.10.0",
|
||||
"tsx": "^4.19.2",
|
||||
"typescript": "^5.7.2"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### tsconfig.json
|
||||
|
||||
```json
|
||||
{
|
||||
"compilerOptions": {
|
||||
"target": "ES2022",
|
||||
"module": "Node16",
|
||||
"moduleResolution": "Node16",
|
||||
"lib": ["ES2022"],
|
||||
"outDir": "./dist",
|
||||
"rootDir": "./src",
|
||||
"strict": true,
|
||||
"esModuleInterop": true,
|
||||
"skipLibCheck": true,
|
||||
"forceConsistentCasingInFileNames": true,
|
||||
"declaration": true,
|
||||
"declarationMap": true,
|
||||
"sourceMap": true,
|
||||
"allowSyntheticDefaultImports": true
|
||||
},
|
||||
"include": ["src/**/*"],
|
||||
"exclude": ["node_modules", "dist"]
|
||||
}
|
||||
```
|
||||
|
||||
## Complete Example
|
||||
|
||||
```typescript
|
||||
#!/usr/bin/env node
|
||||
/**
|
||||
* MCP Server for Example Service.
|
||||
*
|
||||
* This server provides tools to interact with Example API, including user search,
|
||||
* project management, and data export capabilities.
|
||||
*/
|
||||
|
||||
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
|
||||
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
|
||||
import { z } from "zod";
|
||||
import axios, { AxiosError } from "axios";
|
||||
|
||||
// Constants
|
||||
const API_BASE_URL = "https://api.example.com/v1";
|
||||
const CHARACTER_LIMIT = 25000;
|
||||
|
||||
// Enums
|
||||
enum ResponseFormat {
|
||||
MARKDOWN = "markdown",
|
||||
JSON = "json"
|
||||
}
|
||||
|
||||
// Zod schemas
|
||||
const UserSearchInputSchema = z.object({
|
||||
query: z.string()
|
||||
.min(2, "Query must be at least 2 characters")
|
||||
.max(200, "Query must not exceed 200 characters")
|
||||
.describe("Search string to match against names/emails"),
|
||||
limit: z.number()
|
||||
.int()
|
||||
.min(1)
|
||||
.max(100)
|
||||
.default(20)
|
||||
.describe("Maximum results to return"),
|
||||
offset: z.number()
|
||||
.int()
|
||||
.min(0)
|
||||
.default(0)
|
||||
.describe("Number of results to skip for pagination"),
|
||||
response_format: z.nativeEnum(ResponseFormat)
|
||||
.default(ResponseFormat.MARKDOWN)
|
||||
.describe("Output format: 'markdown' for human-readable or 'json' for machine-readable")
|
||||
}).strict();
|
||||
|
||||
type UserSearchInput = z.infer<typeof UserSearchInputSchema>;
|
||||
|
||||
// Shared utility functions
|
||||
async function makeApiRequest<T>(
|
||||
endpoint: string,
|
||||
method: "GET" | "POST" | "PUT" | "DELETE" = "GET",
|
||||
data?: any,
|
||||
params?: any
|
||||
): Promise<T> {
|
||||
try {
|
||||
const response = await axios({
|
||||
method,
|
||||
url: `${API_BASE_URL}/${endpoint}`,
|
||||
data,
|
||||
params,
|
||||
timeout: 30000,
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
"Accept": "application/json"
|
||||
}
|
||||
});
|
||||
return response.data;
|
||||
} catch (error) {
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
function handleApiError(error: unknown): string {
|
||||
if (error instanceof AxiosError) {
|
||||
if (error.response) {
|
||||
switch (error.response.status) {
|
||||
case 404:
|
||||
return "Error: Resource not found. Please check the ID is correct.";
|
||||
case 403:
|
||||
return "Error: Permission denied. You don't have access to this resource.";
|
||||
case 429:
|
||||
return "Error: Rate limit exceeded. Please wait before making more requests.";
|
||||
default:
|
||||
return `Error: API request failed with status ${error.response.status}`;
|
||||
}
|
||||
} else if (error.code === "ECONNABORTED") {
|
||||
return "Error: Request timed out. Please try again.";
|
||||
}
|
||||
}
|
||||
return `Error: Unexpected error occurred: ${error instanceof Error ? error.message : String(error)}`;
|
||||
}
|
||||
|
||||
// Create MCP server instance
|
||||
const server = new McpServer({
|
||||
name: "example-mcp",
|
||||
version: "1.0.0"
|
||||
});
|
||||
|
||||
// Register tools
|
||||
server.registerTool(
|
||||
"example_search_users",
|
||||
{
|
||||
title: "Search Example Users",
|
||||
description: `[Full description as shown above]`,
|
||||
inputSchema: UserSearchInputSchema,
|
||||
annotations: {
|
||||
readOnlyHint: true,
|
||||
destructiveHint: false,
|
||||
idempotentHint: true,
|
||||
openWorldHint: true
|
||||
}
|
||||
},
|
||||
async (params: UserSearchInput) => {
|
||||
// Implementation as shown above
|
||||
}
|
||||
);
|
||||
|
||||
// Main function
|
||||
// For stdio (local):
|
||||
async function runStdio() {
|
||||
if (!process.env.EXAMPLE_API_KEY) {
|
||||
console.error("ERROR: EXAMPLE_API_KEY environment variable is required");
|
||||
process.exit(1);
|
||||
}
|
||||
|
||||
const transport = new StdioServerTransport();
|
||||
await server.connect(transport);
|
||||
console.error("MCP server running via stdio");
|
||||
}
|
||||
|
||||
// For streamable HTTP (remote):
|
||||
async function runHTTP() {
|
||||
if (!process.env.EXAMPLE_API_KEY) {
|
||||
console.error("ERROR: EXAMPLE_API_KEY environment variable is required");
|
||||
process.exit(1);
|
||||
}
|
||||
|
||||
const app = express();
|
||||
app.use(express.json());
|
||||
|
||||
app.post('/mcp', async (req, res) => {
|
||||
const transport = new StreamableHTTPServerTransport({
|
||||
sessionIdGenerator: undefined,
|
||||
enableJsonResponse: true
|
||||
});
|
||||
res.on('close', () => transport.close());
|
||||
await server.connect(transport);
|
||||
await transport.handleRequest(req, res, req.body);
|
||||
});
|
||||
|
||||
const port = parseInt(process.env.PORT || '3000');
|
||||
app.listen(port, () => {
|
||||
console.error(`MCP server running on http://localhost:${port}/mcp`);
|
||||
});
|
||||
}
|
||||
|
||||
// Choose transport based on environment
|
||||
const transport = process.env.TRANSPORT || 'stdio';
|
||||
if (transport === 'http') {
|
||||
runHTTP().catch(error => {
|
||||
console.error("Server error:", error);
|
||||
process.exit(1);
|
||||
});
|
||||
} else {
|
||||
runStdio().catch(error => {
|
||||
console.error("Server error:", error);
|
||||
process.exit(1);
|
||||
});
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Advanced MCP Features
|
||||
|
||||
### Resource Registration
|
||||
|
||||
Expose data as resources for efficient, URI-based access:
|
||||
|
||||
```typescript
|
||||
import { ResourceTemplate } from "@modelcontextprotocol/sdk/types.js";
|
||||
|
||||
// Register a resource with URI template
|
||||
server.registerResource(
|
||||
{
|
||||
uri: "file://documents/{name}",
|
||||
name: "Document Resource",
|
||||
description: "Access documents by name",
|
||||
mimeType: "text/plain"
|
||||
},
|
||||
async (uri: string) => {
|
||||
// Extract parameter from URI
|
||||
const match = uri.match(/^file:\/\/documents\/(.+)$/);
|
||||
if (!match) {
|
||||
throw new Error("Invalid URI format");
|
||||
}
|
||||
|
||||
const documentName = match[1];
|
||||
const content = await loadDocument(documentName);
|
||||
|
||||
return {
|
||||
contents: [{
|
||||
uri,
|
||||
mimeType: "text/plain",
|
||||
text: content
|
||||
}]
|
||||
};
|
||||
}
|
||||
);
|
||||
|
||||
// List available resources dynamically
|
||||
server.registerResourceList(async () => {
|
||||
const documents = await getAvailableDocuments();
|
||||
return {
|
||||
resources: documents.map(doc => ({
|
||||
uri: `file://documents/${doc.name}`,
|
||||
name: doc.name,
|
||||
mimeType: "text/plain",
|
||||
description: doc.description
|
||||
}))
|
||||
};
|
||||
});
|
||||
```
|
||||
|
||||
**When to use Resources vs Tools:**
|
||||
- **Resources**: For data access with simple URI-based parameters
|
||||
- **Tools**: For complex operations requiring validation and business logic
|
||||
- **Resources**: When data is relatively static or template-based
|
||||
- **Tools**: When operations have side effects or complex workflows
|
||||
|
||||
### Transport Options
|
||||
|
||||
The TypeScript SDK supports two main transport mechanisms:
|
||||
|
||||
#### Streamable HTTP (Recommended for Remote Servers)
|
||||
|
||||
```typescript
|
||||
import { StreamableHTTPServerTransport } from "@modelcontextprotocol/sdk/server/streamableHttp.js";
|
||||
import express from "express";
|
||||
|
||||
const app = express();
|
||||
app.use(express.json());
|
||||
|
||||
app.post('/mcp', async (req, res) => {
|
||||
// Create new transport for each request (stateless, prevents request ID collisions)
|
||||
const transport = new StreamableHTTPServerTransport({
|
||||
sessionIdGenerator: undefined,
|
||||
enableJsonResponse: true
|
||||
});
|
||||
|
||||
res.on('close', () => transport.close());
|
||||
|
||||
await server.connect(transport);
|
||||
await transport.handleRequest(req, res, req.body);
|
||||
});
|
||||
|
||||
app.listen(3000);
|
||||
```
|
||||
|
||||
#### stdio (For Local Integrations)
|
||||
|
||||
```typescript
|
||||
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
|
||||
|
||||
const transport = new StdioServerTransport();
|
||||
await server.connect(transport);
|
||||
```
|
||||
|
||||
**Transport selection:**
|
||||
- **Streamable HTTP**: Web services, remote access, multiple clients
|
||||
- **stdio**: Command-line tools, local development, subprocess integration
|
||||
|
||||
### Notification Support
|
||||
|
||||
Notify clients when server state changes:
|
||||
|
||||
```typescript
|
||||
// Notify when tools list changes
|
||||
server.notification({
|
||||
method: "notifications/tools/list_changed"
|
||||
});
|
||||
|
||||
// Notify when resources change
|
||||
server.notification({
|
||||
method: "notifications/resources/list_changed"
|
||||
});
|
||||
```
|
||||
|
||||
Use notifications sparingly - only when server capabilities genuinely change.
|
||||
|
||||
---
|
||||
|
||||
## Code Best Practices
|
||||
|
||||
### Code Composability and Reusability
|
||||
|
||||
Your implementation MUST prioritize composability and code reuse:
|
||||
|
||||
1. **Extract Common Functionality**:
|
||||
- Create reusable helper functions for operations used across multiple tools
|
||||
- Build shared API clients for HTTP requests instead of duplicating code
|
||||
- Centralize error handling logic in utility functions
|
||||
- Extract business logic into dedicated functions that can be composed
|
||||
- Extract shared markdown or JSON field selection & formatting functionality
|
||||
|
||||
2. **Avoid Duplication**:
|
||||
- NEVER copy-paste similar code between tools
|
||||
- If you find yourself writing similar logic twice, extract it into a function
|
||||
- Common operations like pagination, filtering, field selection, and formatting should be shared
|
||||
- Authentication/authorization logic should be centralized
|
||||
|
||||
## Building and Running
|
||||
|
||||
Always build your TypeScript code before running:
|
||||
|
||||
```bash
|
||||
# Build the project
|
||||
npm run build
|
||||
|
||||
# Run the server
|
||||
npm start
|
||||
|
||||
# Development with auto-reload
|
||||
npm run dev
|
||||
```
|
||||
|
||||
Always ensure `npm run build` completes successfully before considering the implementation complete.
|
||||
|
||||
## Quality Checklist
|
||||
|
||||
Before finalizing your Node/TypeScript MCP server implementation, ensure:
|
||||
|
||||
### Strategic Design
|
||||
- [ ] Tools enable complete workflows, not just API endpoint wrappers
|
||||
- [ ] Tool names reflect natural task subdivisions
|
||||
- [ ] Response formats optimize for agent context efficiency
|
||||
- [ ] Human-readable identifiers used where appropriate
|
||||
- [ ] Error messages guide agents toward correct usage
|
||||
|
||||
### Implementation Quality
|
||||
- [ ] FOCUSED IMPLEMENTATION: Most important and valuable tools implemented
|
||||
- [ ] All tools registered using `registerTool` with complete configuration
|
||||
- [ ] All tools include `title`, `description`, `inputSchema`, and `annotations`
|
||||
- [ ] Annotations correctly set (readOnlyHint, destructiveHint, idempotentHint, openWorldHint)
|
||||
- [ ] All tools use Zod schemas for runtime input validation with `.strict()` enforcement
|
||||
- [ ] All Zod schemas have proper constraints and descriptive error messages
|
||||
- [ ] All tools have comprehensive descriptions with explicit input/output types
|
||||
- [ ] Descriptions include return value examples and complete schema documentation
|
||||
- [ ] Error messages are clear, actionable, and educational
|
||||
|
||||
### TypeScript Quality
|
||||
- [ ] TypeScript interfaces are defined for all data structures
|
||||
- [ ] Strict TypeScript is enabled in tsconfig.json
|
||||
- [ ] No use of `any` type - use `unknown` or proper types instead
|
||||
- [ ] All async functions have explicit Promise<T> return types
|
||||
- [ ] Error handling uses proper type guards (e.g., `axios.isAxiosError`, `z.ZodError`)
|
||||
|
||||
### Advanced Features (where applicable)
|
||||
- [ ] Resources registered for appropriate data endpoints
|
||||
- [ ] Appropriate transport configured (stdio or streamable HTTP)
|
||||
- [ ] Notifications implemented for dynamic server capabilities
|
||||
- [ ] Type-safe with SDK interfaces
|
||||
|
||||
### Project Configuration
|
||||
- [ ] Package.json includes all necessary dependencies
|
||||
- [ ] Build script produces working JavaScript in dist/ directory
|
||||
- [ ] Main entry point is properly configured as dist/index.js
|
||||
- [ ] Server name follows format: `{service}-mcp-server`
|
||||
- [ ] tsconfig.json properly configured with strict mode
|
||||
|
||||
### Code Quality
|
||||
- [ ] Pagination is properly implemented where applicable
|
||||
- [ ] Large responses check CHARACTER_LIMIT constant and truncate with clear messages
|
||||
- [ ] Filtering options are provided for potentially large result sets
|
||||
- [ ] All network operations handle timeouts and connection errors gracefully
|
||||
- [ ] Common functionality is extracted into reusable functions
|
||||
- [ ] Return types are consistent across similar operations
|
||||
|
||||
### Testing and Build
|
||||
- [ ] `npm run build` completes successfully without errors
|
||||
- [ ] dist/index.js created and executable
|
||||
- [ ] Server runs: `node dist/index.js --help`
|
||||
- [ ] All imports resolve correctly
|
||||
- [ ] Sample tool calls work as expected
|
||||
@@ -0,0 +1,719 @@
|
||||
# Python MCP Server Implementation Guide
|
||||
|
||||
## Overview
|
||||
|
||||
This document provides Python-specific best practices and examples for implementing MCP servers using the MCP Python SDK. It covers server setup, tool registration patterns, input validation with Pydantic, error handling, and complete working examples.
|
||||
|
||||
---
|
||||
|
||||
## Quick Reference
|
||||
|
||||
### Key Imports
|
||||
```python
|
||||
from mcp.server.fastmcp import FastMCP
|
||||
from pydantic import BaseModel, Field, field_validator, ConfigDict
|
||||
from typing import Optional, List, Dict, Any
|
||||
from enum import Enum
|
||||
import httpx
|
||||
```
|
||||
|
||||
### Server Initialization
|
||||
```python
|
||||
mcp = FastMCP("service_mcp")
|
||||
```
|
||||
|
||||
### Tool Registration Pattern
|
||||
```python
|
||||
@mcp.tool(name="tool_name", annotations={...})
|
||||
async def tool_function(params: InputModel) -> str:
|
||||
# Implementation
|
||||
pass
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## MCP Python SDK and FastMCP
|
||||
|
||||
The official MCP Python SDK provides FastMCP, a high-level framework for building MCP servers. It provides:
|
||||
- Automatic description and inputSchema generation from function signatures and docstrings
|
||||
- Pydantic model integration for input validation
|
||||
- Decorator-based tool registration with `@mcp.tool`
|
||||
|
||||
**For complete SDK documentation, use WebFetch to load:**
|
||||
`https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md`
|
||||
|
||||
## Server Naming Convention
|
||||
|
||||
Python MCP servers must follow this naming pattern:
|
||||
- **Format**: `{service}_mcp` (lowercase with underscores)
|
||||
- **Examples**: `github_mcp`, `jira_mcp`, `stripe_mcp`
|
||||
|
||||
The name should be:
|
||||
- General (not tied to specific features)
|
||||
- Descriptive of the service/API being integrated
|
||||
- Easy to infer from the task description
|
||||
- Without version numbers or dates
|
||||
|
||||
## Tool Implementation
|
||||
|
||||
### Tool Naming
|
||||
|
||||
Use snake_case for tool names (e.g., "search_users", "create_project", "get_channel_info") with clear, action-oriented names.
|
||||
|
||||
**Avoid Naming Conflicts**: Include the service context to prevent overlaps:
|
||||
- Use "slack_send_message" instead of just "send_message"
|
||||
- Use "github_create_issue" instead of just "create_issue"
|
||||
- Use "asana_list_tasks" instead of just "list_tasks"
|
||||
|
||||
### Tool Structure with FastMCP
|
||||
|
||||
Tools are defined using the `@mcp.tool` decorator with Pydantic models for input validation:
|
||||
|
||||
```python
|
||||
from pydantic import BaseModel, Field, ConfigDict
|
||||
from mcp.server.fastmcp import FastMCP
|
||||
|
||||
# Initialize the MCP server
|
||||
mcp = FastMCP("example_mcp")
|
||||
|
||||
# Define Pydantic model for input validation
|
||||
class ServiceToolInput(BaseModel):
|
||||
'''Input model for service tool operation.'''
|
||||
model_config = ConfigDict(
|
||||
str_strip_whitespace=True, # Auto-strip whitespace from strings
|
||||
validate_assignment=True, # Validate on assignment
|
||||
extra='forbid' # Forbid extra fields
|
||||
)
|
||||
|
||||
param1: str = Field(..., description="First parameter description (e.g., 'user123', 'project-abc')", min_length=1, max_length=100)
|
||||
param2: Optional[int] = Field(default=None, description="Optional integer parameter with constraints", ge=0, le=1000)
|
||||
tags: Optional[List[str]] = Field(default_factory=list, description="List of tags to apply", max_items=10)
|
||||
|
||||
@mcp.tool(
|
||||
name="service_tool_name",
|
||||
annotations={
|
||||
"title": "Human-Readable Tool Title",
|
||||
"readOnlyHint": True, # Tool does not modify environment
|
||||
"destructiveHint": False, # Tool does not perform destructive operations
|
||||
"idempotentHint": True, # Repeated calls have no additional effect
|
||||
"openWorldHint": False # Tool does not interact with external entities
|
||||
}
|
||||
)
|
||||
async def service_tool_name(params: ServiceToolInput) -> str:
|
||||
'''Tool description automatically becomes the 'description' field.
|
||||
|
||||
This tool performs a specific operation on the service. It validates all inputs
|
||||
using the ServiceToolInput Pydantic model before processing.
|
||||
|
||||
Args:
|
||||
params (ServiceToolInput): Validated input parameters containing:
|
||||
- param1 (str): First parameter description
|
||||
- param2 (Optional[int]): Optional parameter with default
|
||||
- tags (Optional[List[str]]): List of tags
|
||||
|
||||
Returns:
|
||||
str: JSON-formatted response containing operation results
|
||||
'''
|
||||
# Implementation here
|
||||
pass
|
||||
```
|
||||
|
||||
## Pydantic v2 Key Features
|
||||
|
||||
- Use `model_config` instead of nested `Config` class
|
||||
- Use `field_validator` instead of deprecated `validator`
|
||||
- Use `model_dump()` instead of deprecated `dict()`
|
||||
- Validators require `@classmethod` decorator
|
||||
- Type hints are required for validator methods
|
||||
|
||||
```python
|
||||
from pydantic import BaseModel, Field, field_validator, ConfigDict
|
||||
|
||||
class CreateUserInput(BaseModel):
|
||||
model_config = ConfigDict(
|
||||
str_strip_whitespace=True,
|
||||
validate_assignment=True
|
||||
)
|
||||
|
||||
name: str = Field(..., description="User's full name", min_length=1, max_length=100)
|
||||
email: str = Field(..., description="User's email address", pattern=r'^[\w\.-]+@[\w\.-]+\.\w+$')
|
||||
age: int = Field(..., description="User's age", ge=0, le=150)
|
||||
|
||||
@field_validator('email')
|
||||
@classmethod
|
||||
def validate_email(cls, v: str) -> str:
|
||||
if not v.strip():
|
||||
raise ValueError("Email cannot be empty")
|
||||
return v.lower()
|
||||
```
|
||||
|
||||
## Response Format Options
|
||||
|
||||
Support multiple output formats for flexibility:
|
||||
|
||||
```python
|
||||
from enum import Enum
|
||||
|
||||
class ResponseFormat(str, Enum):
|
||||
'''Output format for tool responses.'''
|
||||
MARKDOWN = "markdown"
|
||||
JSON = "json"
|
||||
|
||||
class UserSearchInput(BaseModel):
|
||||
query: str = Field(..., description="Search query")
|
||||
response_format: ResponseFormat = Field(
|
||||
default=ResponseFormat.MARKDOWN,
|
||||
description="Output format: 'markdown' for human-readable or 'json' for machine-readable"
|
||||
)
|
||||
```
|
||||
|
||||
**Markdown format**:
|
||||
- Use headers, lists, and formatting for clarity
|
||||
- Convert timestamps to human-readable format (e.g., "2024-01-15 10:30:00 UTC" instead of epoch)
|
||||
- Show display names with IDs in parentheses (e.g., "@john.doe (U123456)")
|
||||
- Omit verbose metadata (e.g., show only one profile image URL, not all sizes)
|
||||
- Group related information logically
|
||||
|
||||
**JSON format**:
|
||||
- Return complete, structured data suitable for programmatic processing
|
||||
- Include all available fields and metadata
|
||||
- Use consistent field names and types
|
||||
|
||||
## Pagination Implementation
|
||||
|
||||
For tools that list resources:
|
||||
|
||||
```python
|
||||
class ListInput(BaseModel):
|
||||
limit: Optional[int] = Field(default=20, description="Maximum results to return", ge=1, le=100)
|
||||
offset: Optional[int] = Field(default=0, description="Number of results to skip for pagination", ge=0)
|
||||
|
||||
async def list_items(params: ListInput) -> str:
|
||||
# Make API request with pagination
|
||||
data = await api_request(limit=params.limit, offset=params.offset)
|
||||
|
||||
# Return pagination info
|
||||
response = {
|
||||
"total": data["total"],
|
||||
"count": len(data["items"]),
|
||||
"offset": params.offset,
|
||||
"items": data["items"],
|
||||
"has_more": data["total"] > params.offset + len(data["items"]),
|
||||
"next_offset": params.offset + len(data["items"]) if data["total"] > params.offset + len(data["items"]) else None
|
||||
}
|
||||
return json.dumps(response, indent=2)
|
||||
```
|
||||
|
||||
## Error Handling
|
||||
|
||||
Provide clear, actionable error messages:
|
||||
|
||||
```python
|
||||
def _handle_api_error(e: Exception) -> str:
|
||||
'''Consistent error formatting across all tools.'''
|
||||
if isinstance(e, httpx.HTTPStatusError):
|
||||
if e.response.status_code == 404:
|
||||
return "Error: Resource not found. Please check the ID is correct."
|
||||
elif e.response.status_code == 403:
|
||||
return "Error: Permission denied. You don't have access to this resource."
|
||||
elif e.response.status_code == 429:
|
||||
return "Error: Rate limit exceeded. Please wait before making more requests."
|
||||
return f"Error: API request failed with status {e.response.status_code}"
|
||||
elif isinstance(e, httpx.TimeoutException):
|
||||
return "Error: Request timed out. Please try again."
|
||||
return f"Error: Unexpected error occurred: {type(e).__name__}"
|
||||
```
|
||||
|
||||
## Shared Utilities
|
||||
|
||||
Extract common functionality into reusable functions:
|
||||
|
||||
```python
|
||||
# Shared API request function
|
||||
async def _make_api_request(endpoint: str, method: str = "GET", **kwargs) -> dict:
|
||||
'''Reusable function for all API calls.'''
|
||||
async with httpx.AsyncClient() as client:
|
||||
response = await client.request(
|
||||
method,
|
||||
f"{API_BASE_URL}/{endpoint}",
|
||||
timeout=30.0,
|
||||
**kwargs
|
||||
)
|
||||
response.raise_for_status()
|
||||
return response.json()
|
||||
```
|
||||
|
||||
## Async/Await Best Practices
|
||||
|
||||
Always use async/await for network requests and I/O operations:
|
||||
|
||||
```python
|
||||
# Good: Async network request
|
||||
async def fetch_data(resource_id: str) -> dict:
|
||||
async with httpx.AsyncClient() as client:
|
||||
response = await client.get(f"{API_URL}/resource/{resource_id}")
|
||||
response.raise_for_status()
|
||||
return response.json()
|
||||
|
||||
# Bad: Synchronous request
|
||||
def fetch_data(resource_id: str) -> dict:
|
||||
response = requests.get(f"{API_URL}/resource/{resource_id}") # Blocks
|
||||
return response.json()
|
||||
```
|
||||
|
||||
## Type Hints
|
||||
|
||||
Use type hints throughout:
|
||||
|
||||
```python
|
||||
from typing import Optional, List, Dict, Any
|
||||
|
||||
async def get_user(user_id: str) -> Dict[str, Any]:
|
||||
data = await fetch_user(user_id)
|
||||
return {"id": data["id"], "name": data["name"]}
|
||||
```
|
||||
|
||||
## Tool Docstrings
|
||||
|
||||
Every tool must have comprehensive docstrings with explicit type information:
|
||||
|
||||
```python
|
||||
async def search_users(params: UserSearchInput) -> str:
|
||||
'''
|
||||
Search for users in the Example system by name, email, or team.
|
||||
|
||||
This tool searches across all user profiles in the Example platform,
|
||||
supporting partial matches and various search filters. It does NOT
|
||||
create or modify users, only searches existing ones.
|
||||
|
||||
Args:
|
||||
params (UserSearchInput): Validated input parameters containing:
|
||||
- query (str): Search string to match against names/emails (e.g., "john", "@example.com", "team:marketing")
|
||||
- limit (Optional[int]): Maximum results to return, between 1-100 (default: 20)
|
||||
- offset (Optional[int]): Number of results to skip for pagination (default: 0)
|
||||
|
||||
Returns:
|
||||
str: JSON-formatted string containing search results with the following schema:
|
||||
|
||||
Success response:
|
||||
{
|
||||
"total": int, # Total number of matches found
|
||||
"count": int, # Number of results in this response
|
||||
"offset": int, # Current pagination offset
|
||||
"users": [
|
||||
{
|
||||
"id": str, # User ID (e.g., "U123456789")
|
||||
"name": str, # Full name (e.g., "John Doe")
|
||||
"email": str, # Email address (e.g., "john@example.com")
|
||||
"team": str # Team name (e.g., "Marketing") - optional
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
Error response:
|
||||
"Error: <error message>" or "No users found matching '<query>'"
|
||||
|
||||
Examples:
|
||||
- Use when: "Find all marketing team members" -> params with query="team:marketing"
|
||||
- Use when: "Search for John's account" -> params with query="john"
|
||||
- Don't use when: You need to create a user (use example_create_user instead)
|
||||
- Don't use when: You have a user ID and need full details (use example_get_user instead)
|
||||
|
||||
Error Handling:
|
||||
- Input validation errors are handled by Pydantic model
|
||||
- Returns "Error: Rate limit exceeded" if too many requests (429 status)
|
||||
- Returns "Error: Invalid API authentication" if API key is invalid (401 status)
|
||||
- Returns formatted list of results or "No users found matching 'query'"
|
||||
'''
|
||||
```
|
||||
|
||||
## Complete Example
|
||||
|
||||
See below for a complete Python MCP server example:
|
||||
|
||||
```python
|
||||
#!/usr/bin/env python3
|
||||
'''
|
||||
MCP Server for Example Service.
|
||||
|
||||
This server provides tools to interact with Example API, including user search,
|
||||
project management, and data export capabilities.
|
||||
'''
|
||||
|
||||
from typing import Optional, List, Dict, Any
|
||||
from enum import Enum
|
||||
import httpx
|
||||
from pydantic import BaseModel, Field, field_validator, ConfigDict
|
||||
from mcp.server.fastmcp import FastMCP
|
||||
|
||||
# Initialize the MCP server
|
||||
mcp = FastMCP("example_mcp")
|
||||
|
||||
# Constants
|
||||
API_BASE_URL = "https://api.example.com/v1"
|
||||
|
||||
# Enums
|
||||
class ResponseFormat(str, Enum):
|
||||
'''Output format for tool responses.'''
|
||||
MARKDOWN = "markdown"
|
||||
JSON = "json"
|
||||
|
||||
# Pydantic Models for Input Validation
|
||||
class UserSearchInput(BaseModel):
|
||||
'''Input model for user search operations.'''
|
||||
model_config = ConfigDict(
|
||||
str_strip_whitespace=True,
|
||||
validate_assignment=True
|
||||
)
|
||||
|
||||
query: str = Field(..., description="Search string to match against names/emails", min_length=2, max_length=200)
|
||||
limit: Optional[int] = Field(default=20, description="Maximum results to return", ge=1, le=100)
|
||||
offset: Optional[int] = Field(default=0, description="Number of results to skip for pagination", ge=0)
|
||||
response_format: ResponseFormat = Field(default=ResponseFormat.MARKDOWN, description="Output format")
|
||||
|
||||
@field_validator('query')
|
||||
@classmethod
|
||||
def validate_query(cls, v: str) -> str:
|
||||
if not v.strip():
|
||||
raise ValueError("Query cannot be empty or whitespace only")
|
||||
return v.strip()
|
||||
|
||||
# Shared utility functions
|
||||
async def _make_api_request(endpoint: str, method: str = "GET", **kwargs) -> dict:
|
||||
'''Reusable function for all API calls.'''
|
||||
async with httpx.AsyncClient() as client:
|
||||
response = await client.request(
|
||||
method,
|
||||
f"{API_BASE_URL}/{endpoint}",
|
||||
timeout=30.0,
|
||||
**kwargs
|
||||
)
|
||||
response.raise_for_status()
|
||||
return response.json()
|
||||
|
||||
def _handle_api_error(e: Exception) -> str:
|
||||
'''Consistent error formatting across all tools.'''
|
||||
if isinstance(e, httpx.HTTPStatusError):
|
||||
if e.response.status_code == 404:
|
||||
return "Error: Resource not found. Please check the ID is correct."
|
||||
elif e.response.status_code == 403:
|
||||
return "Error: Permission denied. You don't have access to this resource."
|
||||
elif e.response.status_code == 429:
|
||||
return "Error: Rate limit exceeded. Please wait before making more requests."
|
||||
return f"Error: API request failed with status {e.response.status_code}"
|
||||
elif isinstance(e, httpx.TimeoutException):
|
||||
return "Error: Request timed out. Please try again."
|
||||
return f"Error: Unexpected error occurred: {type(e).__name__}"
|
||||
|
||||
# Tool definitions
|
||||
@mcp.tool(
|
||||
name="example_search_users",
|
||||
annotations={
|
||||
"title": "Search Example Users",
|
||||
"readOnlyHint": True,
|
||||
"destructiveHint": False,
|
||||
"idempotentHint": True,
|
||||
"openWorldHint": True
|
||||
}
|
||||
)
|
||||
async def example_search_users(params: UserSearchInput) -> str:
|
||||
'''Search for users in the Example system by name, email, or team.
|
||||
|
||||
[Full docstring as shown above]
|
||||
'''
|
||||
try:
|
||||
# Make API request using validated parameters
|
||||
data = await _make_api_request(
|
||||
"users/search",
|
||||
params={
|
||||
"q": params.query,
|
||||
"limit": params.limit,
|
||||
"offset": params.offset
|
||||
}
|
||||
)
|
||||
|
||||
users = data.get("users", [])
|
||||
total = data.get("total", 0)
|
||||
|
||||
if not users:
|
||||
return f"No users found matching '{params.query}'"
|
||||
|
||||
# Format response based on requested format
|
||||
if params.response_format == ResponseFormat.MARKDOWN:
|
||||
lines = [f"# User Search Results: '{params.query}'", ""]
|
||||
lines.append(f"Found {total} users (showing {len(users)})")
|
||||
lines.append("")
|
||||
|
||||
for user in users:
|
||||
lines.append(f"## {user['name']} ({user['id']})")
|
||||
lines.append(f"- **Email**: {user['email']}")
|
||||
if user.get('team'):
|
||||
lines.append(f"- **Team**: {user['team']}")
|
||||
lines.append("")
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
else:
|
||||
# Machine-readable JSON format
|
||||
import json
|
||||
response = {
|
||||
"total": total,
|
||||
"count": len(users),
|
||||
"offset": params.offset,
|
||||
"users": users
|
||||
}
|
||||
return json.dumps(response, indent=2)
|
||||
|
||||
except Exception as e:
|
||||
return _handle_api_error(e)
|
||||
|
||||
if __name__ == "__main__":
|
||||
mcp.run()
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Advanced FastMCP Features
|
||||
|
||||
### Context Parameter Injection
|
||||
|
||||
FastMCP can automatically inject a `Context` parameter into tools for advanced capabilities like logging, progress reporting, resource reading, and user interaction:
|
||||
|
||||
```python
|
||||
from mcp.server.fastmcp import FastMCP, Context
|
||||
|
||||
mcp = FastMCP("example_mcp")
|
||||
|
||||
@mcp.tool()
|
||||
async def advanced_search(query: str, ctx: Context) -> str:
|
||||
'''Advanced tool with context access for logging and progress.'''
|
||||
|
||||
# Report progress for long operations
|
||||
await ctx.report_progress(0.25, "Starting search...")
|
||||
|
||||
# Log information for debugging
|
||||
await ctx.log_info("Processing query", {"query": query, "timestamp": datetime.now()})
|
||||
|
||||
# Perform search
|
||||
results = await search_api(query)
|
||||
await ctx.report_progress(0.75, "Formatting results...")
|
||||
|
||||
# Access server configuration
|
||||
server_name = ctx.fastmcp.name
|
||||
|
||||
return format_results(results)
|
||||
|
||||
@mcp.tool()
|
||||
async def interactive_tool(resource_id: str, ctx: Context) -> str:
|
||||
'''Tool that can request additional input from users.'''
|
||||
|
||||
# Request sensitive information when needed
|
||||
api_key = await ctx.elicit(
|
||||
prompt="Please provide your API key:",
|
||||
input_type="password"
|
||||
)
|
||||
|
||||
# Use the provided key
|
||||
return await api_call(resource_id, api_key)
|
||||
```
|
||||
|
||||
**Context capabilities:**
|
||||
- `ctx.report_progress(progress, message)` - Report progress for long operations
|
||||
- `ctx.log_info(message, data)` / `ctx.log_error()` / `ctx.log_debug()` - Logging
|
||||
- `ctx.elicit(prompt, input_type)` - Request input from users
|
||||
- `ctx.fastmcp.name` - Access server configuration
|
||||
- `ctx.read_resource(uri)` - Read MCP resources
|
||||
|
||||
### Resource Registration
|
||||
|
||||
Expose data as resources for efficient, template-based access:
|
||||
|
||||
```python
|
||||
@mcp.resource("file://documents/{name}")
|
||||
async def get_document(name: str) -> str:
|
||||
'''Expose documents as MCP resources.
|
||||
|
||||
Resources are useful for static or semi-static data that doesn't
|
||||
require complex parameters. They use URI templates for flexible access.
|
||||
'''
|
||||
document_path = f"./docs/{name}"
|
||||
with open(document_path, "r") as f:
|
||||
return f.read()
|
||||
|
||||
@mcp.resource("config://settings/{key}")
|
||||
async def get_setting(key: str, ctx: Context) -> str:
|
||||
'''Expose configuration as resources with context.'''
|
||||
settings = await load_settings()
|
||||
return json.dumps(settings.get(key, {}))
|
||||
```
|
||||
|
||||
**When to use Resources vs Tools:**
|
||||
- **Resources**: For data access with simple parameters (URI templates)
|
||||
- **Tools**: For complex operations with validation and business logic
|
||||
|
||||
### Structured Output Types
|
||||
|
||||
FastMCP supports multiple return types beyond strings:
|
||||
|
||||
```python
|
||||
from typing import TypedDict
|
||||
from dataclasses import dataclass
|
||||
from pydantic import BaseModel
|
||||
|
||||
# TypedDict for structured returns
|
||||
class UserData(TypedDict):
|
||||
id: str
|
||||
name: str
|
||||
email: str
|
||||
|
||||
@mcp.tool()
|
||||
async def get_user_typed(user_id: str) -> UserData:
|
||||
'''Returns structured data - FastMCP handles serialization.'''
|
||||
return {"id": user_id, "name": "John Doe", "email": "john@example.com"}
|
||||
|
||||
# Pydantic models for complex validation
|
||||
class DetailedUser(BaseModel):
|
||||
id: str
|
||||
name: str
|
||||
email: str
|
||||
created_at: datetime
|
||||
metadata: Dict[str, Any]
|
||||
|
||||
@mcp.tool()
|
||||
async def get_user_detailed(user_id: str) -> DetailedUser:
|
||||
'''Returns Pydantic model - automatically generates schema.'''
|
||||
user = await fetch_user(user_id)
|
||||
return DetailedUser(**user)
|
||||
```
|
||||
|
||||
### Lifespan Management
|
||||
|
||||
Initialize resources that persist across requests:
|
||||
|
||||
```python
|
||||
from contextlib import asynccontextmanager
|
||||
|
||||
@asynccontextmanager
|
||||
async def app_lifespan():
|
||||
'''Manage resources that live for the server's lifetime.'''
|
||||
# Initialize connections, load config, etc.
|
||||
db = await connect_to_database()
|
||||
config = load_configuration()
|
||||
|
||||
# Make available to all tools
|
||||
yield {"db": db, "config": config}
|
||||
|
||||
# Cleanup on shutdown
|
||||
await db.close()
|
||||
|
||||
mcp = FastMCP("example_mcp", lifespan=app_lifespan)
|
||||
|
||||
@mcp.tool()
|
||||
async def query_data(query: str, ctx: Context) -> str:
|
||||
'''Access lifespan resources through context.'''
|
||||
db = ctx.request_context.lifespan_state["db"]
|
||||
results = await db.query(query)
|
||||
return format_results(results)
|
||||
```
|
||||
|
||||
### Transport Options
|
||||
|
||||
FastMCP supports two main transport mechanisms:
|
||||
|
||||
```python
|
||||
# stdio transport (for local tools) - default
|
||||
if __name__ == "__main__":
|
||||
mcp.run()
|
||||
|
||||
# Streamable HTTP transport (for remote servers)
|
||||
if __name__ == "__main__":
|
||||
mcp.run(transport="streamable_http", port=8000)
|
||||
```
|
||||
|
||||
**Transport selection:**
|
||||
- **stdio**: Command-line tools, local integrations, subprocess execution
|
||||
- **Streamable HTTP**: Web services, remote access, multiple clients
|
||||
|
||||
---
|
||||
|
||||
## Code Best Practices
|
||||
|
||||
### Code Composability and Reusability
|
||||
|
||||
Your implementation MUST prioritize composability and code reuse:
|
||||
|
||||
1. **Extract Common Functionality**:
|
||||
- Create reusable helper functions for operations used across multiple tools
|
||||
- Build shared API clients for HTTP requests instead of duplicating code
|
||||
- Centralize error handling logic in utility functions
|
||||
- Extract business logic into dedicated functions that can be composed
|
||||
- Extract shared markdown or JSON field selection & formatting functionality
|
||||
|
||||
2. **Avoid Duplication**:
|
||||
- NEVER copy-paste similar code between tools
|
||||
- If you find yourself writing similar logic twice, extract it into a function
|
||||
- Common operations like pagination, filtering, field selection, and formatting should be shared
|
||||
- Authentication/authorization logic should be centralized
|
||||
|
||||
### Python-Specific Best Practices
|
||||
|
||||
1. **Use Type Hints**: Always include type annotations for function parameters and return values
|
||||
2. **Pydantic Models**: Define clear Pydantic models for all input validation
|
||||
3. **Avoid Manual Validation**: Let Pydantic handle input validation with constraints
|
||||
4. **Proper Imports**: Group imports (standard library, third-party, local)
|
||||
5. **Error Handling**: Use specific exception types (httpx.HTTPStatusError, not generic Exception)
|
||||
6. **Async Context Managers**: Use `async with` for resources that need cleanup
|
||||
7. **Constants**: Define module-level constants in UPPER_CASE
|
||||
|
||||
## Quality Checklist
|
||||
|
||||
Before finalizing your Python MCP server implementation, ensure:
|
||||
|
||||
### Strategic Design
|
||||
- [ ] Tools enable complete workflows, not just API endpoint wrappers
|
||||
- [ ] Tool names reflect natural task subdivisions
|
||||
- [ ] Response formats optimize for agent context efficiency
|
||||
- [ ] Human-readable identifiers used where appropriate
|
||||
- [ ] Error messages guide agents toward correct usage
|
||||
|
||||
### Implementation Quality
|
||||
- [ ] FOCUSED IMPLEMENTATION: Most important and valuable tools implemented
|
||||
- [ ] All tools have descriptive names and documentation
|
||||
- [ ] Return types are consistent across similar operations
|
||||
- [ ] Error handling is implemented for all external calls
|
||||
- [ ] Server name follows format: `{service}_mcp`
|
||||
- [ ] All network operations use async/await
|
||||
- [ ] Common functionality is extracted into reusable functions
|
||||
- [ ] Error messages are clear, actionable, and educational
|
||||
- [ ] Outputs are properly validated and formatted
|
||||
|
||||
### Tool Configuration
|
||||
- [ ] All tools implement 'name' and 'annotations' in the decorator
|
||||
- [ ] Annotations correctly set (readOnlyHint, destructiveHint, idempotentHint, openWorldHint)
|
||||
- [ ] All tools use Pydantic BaseModel for input validation with Field() definitions
|
||||
- [ ] All Pydantic Fields have explicit types and descriptions with constraints
|
||||
- [ ] All tools have comprehensive docstrings with explicit input/output types
|
||||
- [ ] Docstrings include complete schema structure for dict/JSON returns
|
||||
- [ ] Pydantic models handle input validation (no manual validation needed)
|
||||
|
||||
### Advanced Features (where applicable)
|
||||
- [ ] Context injection used for logging, progress, or elicitation
|
||||
- [ ] Resources registered for appropriate data endpoints
|
||||
- [ ] Lifespan management implemented for persistent connections
|
||||
- [ ] Structured output types used (TypedDict, Pydantic models)
|
||||
- [ ] Appropriate transport configured (stdio or streamable HTTP)
|
||||
|
||||
### Code Quality
|
||||
- [ ] File includes proper imports including Pydantic imports
|
||||
- [ ] Pagination is properly implemented where applicable
|
||||
- [ ] Filtering options are provided for potentially large result sets
|
||||
- [ ] All async functions are properly defined with `async def`
|
||||
- [ ] HTTP client usage follows async patterns with proper context managers
|
||||
- [ ] Type hints are used throughout the code
|
||||
- [ ] Constants are defined at module level in UPPER_CASE
|
||||
|
||||
### Testing
|
||||
- [ ] Server runs successfully: `python your_server.py --help`
|
||||
- [ ] All imports resolve correctly
|
||||
- [ ] Sample tool calls work as expected
|
||||
- [ ] Error scenarios handled gracefully
|
||||
@@ -0,0 +1,151 @@
|
||||
"""Lightweight connection handling for MCP servers."""
|
||||
|
||||
from abc import ABC, abstractmethod
|
||||
from contextlib import AsyncExitStack
|
||||
from typing import Any
|
||||
|
||||
from mcp import ClientSession, StdioServerParameters
|
||||
from mcp.client.sse import sse_client
|
||||
from mcp.client.stdio import stdio_client
|
||||
from mcp.client.streamable_http import streamablehttp_client
|
||||
|
||||
|
||||
class MCPConnection(ABC):
|
||||
"""Base class for MCP server connections."""
|
||||
|
||||
def __init__(self):
|
||||
self.session = None
|
||||
self._stack = None
|
||||
|
||||
@abstractmethod
|
||||
def _create_context(self):
|
||||
"""Create the connection context based on connection type."""
|
||||
|
||||
async def __aenter__(self):
|
||||
"""Initialize MCP server connection."""
|
||||
self._stack = AsyncExitStack()
|
||||
await self._stack.__aenter__()
|
||||
|
||||
try:
|
||||
ctx = self._create_context()
|
||||
result = await self._stack.enter_async_context(ctx)
|
||||
|
||||
if len(result) == 2:
|
||||
read, write = result
|
||||
elif len(result) == 3:
|
||||
read, write, _ = result
|
||||
else:
|
||||
raise ValueError(f"Unexpected context result: {result}")
|
||||
|
||||
session_ctx = ClientSession(read, write)
|
||||
self.session = await self._stack.enter_async_context(session_ctx)
|
||||
await self.session.initialize()
|
||||
return self
|
||||
except BaseException:
|
||||
await self._stack.__aexit__(None, None, None)
|
||||
raise
|
||||
|
||||
async def __aexit__(self, exc_type, exc_val, exc_tb):
|
||||
"""Clean up MCP server connection resources."""
|
||||
if self._stack:
|
||||
await self._stack.__aexit__(exc_type, exc_val, exc_tb)
|
||||
self.session = None
|
||||
self._stack = None
|
||||
|
||||
async def list_tools(self) -> list[dict[str, Any]]:
|
||||
"""Retrieve available tools from the MCP server."""
|
||||
response = await self.session.list_tools()
|
||||
return [
|
||||
{
|
||||
"name": tool.name,
|
||||
"description": tool.description,
|
||||
"input_schema": tool.inputSchema,
|
||||
}
|
||||
for tool in response.tools
|
||||
]
|
||||
|
||||
async def call_tool(self, tool_name: str, arguments: dict[str, Any]) -> Any:
|
||||
"""Call a tool on the MCP server with provided arguments."""
|
||||
result = await self.session.call_tool(tool_name, arguments=arguments)
|
||||
return result.content
|
||||
|
||||
|
||||
class MCPConnectionStdio(MCPConnection):
|
||||
"""MCP connection using standard input/output."""
|
||||
|
||||
def __init__(self, command: str, args: list[str] = None, env: dict[str, str] = None):
|
||||
super().__init__()
|
||||
self.command = command
|
||||
self.args = args or []
|
||||
self.env = env
|
||||
|
||||
def _create_context(self):
|
||||
return stdio_client(
|
||||
StdioServerParameters(command=self.command, args=self.args, env=self.env)
|
||||
)
|
||||
|
||||
|
||||
class MCPConnectionSSE(MCPConnection):
|
||||
"""MCP connection using Server-Sent Events."""
|
||||
|
||||
def __init__(self, url: str, headers: dict[str, str] = None):
|
||||
super().__init__()
|
||||
self.url = url
|
||||
self.headers = headers or {}
|
||||
|
||||
def _create_context(self):
|
||||
return sse_client(url=self.url, headers=self.headers)
|
||||
|
||||
|
||||
class MCPConnectionHTTP(MCPConnection):
|
||||
"""MCP connection using Streamable HTTP."""
|
||||
|
||||
def __init__(self, url: str, headers: dict[str, str] = None):
|
||||
super().__init__()
|
||||
self.url = url
|
||||
self.headers = headers or {}
|
||||
|
||||
def _create_context(self):
|
||||
return streamablehttp_client(url=self.url, headers=self.headers)
|
||||
|
||||
|
||||
def create_connection(
|
||||
transport: str,
|
||||
command: str = None,
|
||||
args: list[str] = None,
|
||||
env: dict[str, str] = None,
|
||||
url: str = None,
|
||||
headers: dict[str, str] = None,
|
||||
) -> MCPConnection:
|
||||
"""Factory function to create the appropriate MCP connection.
|
||||
|
||||
Args:
|
||||
transport: Connection type ("stdio", "sse", or "http")
|
||||
command: Command to run (stdio only)
|
||||
args: Command arguments (stdio only)
|
||||
env: Environment variables (stdio only)
|
||||
url: Server URL (sse and http only)
|
||||
headers: HTTP headers (sse and http only)
|
||||
|
||||
Returns:
|
||||
MCPConnection instance
|
||||
"""
|
||||
transport = transport.lower()
|
||||
|
||||
if transport == "stdio":
|
||||
if not command:
|
||||
raise ValueError("Command is required for stdio transport")
|
||||
return MCPConnectionStdio(command=command, args=args, env=env)
|
||||
|
||||
elif transport == "sse":
|
||||
if not url:
|
||||
raise ValueError("URL is required for sse transport")
|
||||
return MCPConnectionSSE(url=url, headers=headers)
|
||||
|
||||
elif transport in ["http", "streamable_http", "streamable-http"]:
|
||||
if not url:
|
||||
raise ValueError("URL is required for http transport")
|
||||
return MCPConnectionHTTP(url=url, headers=headers)
|
||||
|
||||
else:
|
||||
raise ValueError(f"Unsupported transport type: {transport}. Use 'stdio', 'sse', or 'http'")
|
||||
@@ -0,0 +1,373 @@
|
||||
"""MCP Server Evaluation Harness
|
||||
|
||||
This script evaluates MCP servers by running test questions against them using Claude.
|
||||
"""
|
||||
|
||||
import argparse
|
||||
import asyncio
|
||||
import json
|
||||
import re
|
||||
import sys
|
||||
import time
|
||||
import traceback
|
||||
import xml.etree.ElementTree as ET
|
||||
from pathlib import Path
|
||||
from typing import Any
|
||||
|
||||
from anthropic import Anthropic
|
||||
|
||||
from connections import create_connection
|
||||
|
||||
EVALUATION_PROMPT = """You are an AI assistant with access to tools.
|
||||
|
||||
When given a task, you MUST:
|
||||
1. Use the available tools to complete the task
|
||||
2. Provide summary of each step in your approach, wrapped in <summary> tags
|
||||
3. Provide feedback on the tools provided, wrapped in <feedback> tags
|
||||
4. Provide your final response, wrapped in <response> tags
|
||||
|
||||
Summary Requirements:
|
||||
- In your <summary> tags, you must explain:
|
||||
- The steps you took to complete the task
|
||||
- Which tools you used, in what order, and why
|
||||
- The inputs you provided to each tool
|
||||
- The outputs you received from each tool
|
||||
- A summary for how you arrived at the response
|
||||
|
||||
Feedback Requirements:
|
||||
- In your <feedback> tags, provide constructive feedback on the tools:
|
||||
- Comment on tool names: Are they clear and descriptive?
|
||||
- Comment on input parameters: Are they well-documented? Are required vs optional parameters clear?
|
||||
- Comment on descriptions: Do they accurately describe what the tool does?
|
||||
- Comment on any errors encountered during tool usage: Did the tool fail to execute? Did the tool return too many tokens?
|
||||
- Identify specific areas for improvement and explain WHY they would help
|
||||
- Be specific and actionable in your suggestions
|
||||
|
||||
Response Requirements:
|
||||
- Your response should be concise and directly address what was asked
|
||||
- Always wrap your final response in <response> tags
|
||||
- If you cannot solve the task return <response>NOT_FOUND</response>
|
||||
- For numeric responses, provide just the number
|
||||
- For IDs, provide just the ID
|
||||
- For names or text, provide the exact text requested
|
||||
- Your response should go last"""
|
||||
|
||||
|
||||
def parse_evaluation_file(file_path: Path) -> list[dict[str, Any]]:
|
||||
"""Parse XML evaluation file with qa_pair elements."""
|
||||
try:
|
||||
tree = ET.parse(file_path)
|
||||
root = tree.getroot()
|
||||
evaluations = []
|
||||
|
||||
for qa_pair in root.findall(".//qa_pair"):
|
||||
question_elem = qa_pair.find("question")
|
||||
answer_elem = qa_pair.find("answer")
|
||||
|
||||
if question_elem is not None and answer_elem is not None:
|
||||
evaluations.append({
|
||||
"question": (question_elem.text or "").strip(),
|
||||
"answer": (answer_elem.text or "").strip(),
|
||||
})
|
||||
|
||||
return evaluations
|
||||
except Exception as e:
|
||||
print(f"Error parsing evaluation file {file_path}: {e}")
|
||||
return []
|
||||
|
||||
|
||||
def extract_xml_content(text: str, tag: str) -> str | None:
|
||||
"""Extract content from XML tags."""
|
||||
pattern = rf"<{tag}>(.*?)</{tag}>"
|
||||
matches = re.findall(pattern, text, re.DOTALL)
|
||||
return matches[-1].strip() if matches else None
|
||||
|
||||
|
||||
async def agent_loop(
|
||||
client: Anthropic,
|
||||
model: str,
|
||||
question: str,
|
||||
tools: list[dict[str, Any]],
|
||||
connection: Any,
|
||||
) -> tuple[str, dict[str, Any]]:
|
||||
"""Run the agent loop with MCP tools."""
|
||||
messages = [{"role": "user", "content": question}]
|
||||
|
||||
response = await asyncio.to_thread(
|
||||
client.messages.create,
|
||||
model=model,
|
||||
max_tokens=4096,
|
||||
system=EVALUATION_PROMPT,
|
||||
messages=messages,
|
||||
tools=tools,
|
||||
)
|
||||
|
||||
messages.append({"role": "assistant", "content": response.content})
|
||||
|
||||
tool_metrics = {}
|
||||
|
||||
while response.stop_reason == "tool_use":
|
||||
tool_use = next(block for block in response.content if block.type == "tool_use")
|
||||
tool_name = tool_use.name
|
||||
tool_input = tool_use.input
|
||||
|
||||
tool_start_ts = time.time()
|
||||
try:
|
||||
tool_result = await connection.call_tool(tool_name, tool_input)
|
||||
tool_response = json.dumps(tool_result) if isinstance(tool_result, (dict, list)) else str(tool_result)
|
||||
except Exception as e:
|
||||
tool_response = f"Error executing tool {tool_name}: {str(e)}\n"
|
||||
tool_response += traceback.format_exc()
|
||||
tool_duration = time.time() - tool_start_ts
|
||||
|
||||
if tool_name not in tool_metrics:
|
||||
tool_metrics[tool_name] = {"count": 0, "durations": []}
|
||||
tool_metrics[tool_name]["count"] += 1
|
||||
tool_metrics[tool_name]["durations"].append(tool_duration)
|
||||
|
||||
messages.append({
|
||||
"role": "user",
|
||||
"content": [{
|
||||
"type": "tool_result",
|
||||
"tool_use_id": tool_use.id,
|
||||
"content": tool_response,
|
||||
}]
|
||||
})
|
||||
|
||||
response = await asyncio.to_thread(
|
||||
client.messages.create,
|
||||
model=model,
|
||||
max_tokens=4096,
|
||||
system=EVALUATION_PROMPT,
|
||||
messages=messages,
|
||||
tools=tools,
|
||||
)
|
||||
messages.append({"role": "assistant", "content": response.content})
|
||||
|
||||
response_text = next(
|
||||
(block.text for block in response.content if hasattr(block, "text")),
|
||||
None,
|
||||
)
|
||||
return response_text, tool_metrics
|
||||
|
||||
|
||||
async def evaluate_single_task(
|
||||
client: Anthropic,
|
||||
model: str,
|
||||
qa_pair: dict[str, Any],
|
||||
tools: list[dict[str, Any]],
|
||||
connection: Any,
|
||||
task_index: int,
|
||||
) -> dict[str, Any]:
|
||||
"""Evaluate a single QA pair with the given tools."""
|
||||
start_time = time.time()
|
||||
|
||||
print(f"Task {task_index + 1}: Running task with question: {qa_pair['question']}")
|
||||
response, tool_metrics = await agent_loop(client, model, qa_pair["question"], tools, connection)
|
||||
|
||||
response_value = extract_xml_content(response, "response")
|
||||
summary = extract_xml_content(response, "summary")
|
||||
feedback = extract_xml_content(response, "feedback")
|
||||
|
||||
duration_seconds = time.time() - start_time
|
||||
|
||||
return {
|
||||
"question": qa_pair["question"],
|
||||
"expected": qa_pair["answer"],
|
||||
"actual": response_value,
|
||||
"score": int(response_value == qa_pair["answer"]) if response_value else 0,
|
||||
"total_duration": duration_seconds,
|
||||
"tool_calls": tool_metrics,
|
||||
"num_tool_calls": sum(len(metrics["durations"]) for metrics in tool_metrics.values()),
|
||||
"summary": summary,
|
||||
"feedback": feedback,
|
||||
}
|
||||
|
||||
|
||||
REPORT_HEADER = """
|
||||
# Evaluation Report
|
||||
|
||||
## Summary
|
||||
|
||||
- **Accuracy**: {correct}/{total} ({accuracy:.1f}%)
|
||||
- **Average Task Duration**: {average_duration_s:.2f}s
|
||||
- **Average Tool Calls per Task**: {average_tool_calls:.2f}
|
||||
- **Total Tool Calls**: {total_tool_calls}
|
||||
|
||||
---
|
||||
"""
|
||||
|
||||
TASK_TEMPLATE = """
|
||||
### Task {task_num}
|
||||
|
||||
**Question**: {question}
|
||||
**Ground Truth Answer**: `{expected_answer}`
|
||||
**Actual Answer**: `{actual_answer}`
|
||||
**Correct**: {correct_indicator}
|
||||
**Duration**: {total_duration:.2f}s
|
||||
**Tool Calls**: {tool_calls}
|
||||
|
||||
**Summary**
|
||||
{summary}
|
||||
|
||||
**Feedback**
|
||||
{feedback}
|
||||
|
||||
---
|
||||
"""
|
||||
|
||||
|
||||
async def run_evaluation(
|
||||
eval_path: Path,
|
||||
connection: Any,
|
||||
model: str = "claude-3-7-sonnet-20250219",
|
||||
) -> str:
|
||||
"""Run evaluation with MCP server tools."""
|
||||
print("🚀 Starting Evaluation")
|
||||
|
||||
client = Anthropic()
|
||||
|
||||
tools = await connection.list_tools()
|
||||
print(f"📋 Loaded {len(tools)} tools from MCP server")
|
||||
|
||||
qa_pairs = parse_evaluation_file(eval_path)
|
||||
print(f"📋 Loaded {len(qa_pairs)} evaluation tasks")
|
||||
|
||||
results = []
|
||||
for i, qa_pair in enumerate(qa_pairs):
|
||||
print(f"Processing task {i + 1}/{len(qa_pairs)}")
|
||||
result = await evaluate_single_task(client, model, qa_pair, tools, connection, i)
|
||||
results.append(result)
|
||||
|
||||
correct = sum(r["score"] for r in results)
|
||||
accuracy = (correct / len(results)) * 100 if results else 0
|
||||
average_duration_s = sum(r["total_duration"] for r in results) / len(results) if results else 0
|
||||
average_tool_calls = sum(r["num_tool_calls"] for r in results) / len(results) if results else 0
|
||||
total_tool_calls = sum(r["num_tool_calls"] for r in results)
|
||||
|
||||
report = REPORT_HEADER.format(
|
||||
correct=correct,
|
||||
total=len(results),
|
||||
accuracy=accuracy,
|
||||
average_duration_s=average_duration_s,
|
||||
average_tool_calls=average_tool_calls,
|
||||
total_tool_calls=total_tool_calls,
|
||||
)
|
||||
|
||||
report += "".join([
|
||||
TASK_TEMPLATE.format(
|
||||
task_num=i + 1,
|
||||
question=qa_pair["question"],
|
||||
expected_answer=qa_pair["answer"],
|
||||
actual_answer=result["actual"] or "N/A",
|
||||
correct_indicator="✅" if result["score"] else "❌",
|
||||
total_duration=result["total_duration"],
|
||||
tool_calls=json.dumps(result["tool_calls"], indent=2),
|
||||
summary=result["summary"] or "N/A",
|
||||
feedback=result["feedback"] or "N/A",
|
||||
)
|
||||
for i, (qa_pair, result) in enumerate(zip(qa_pairs, results))
|
||||
])
|
||||
|
||||
return report
|
||||
|
||||
|
||||
def parse_headers(header_list: list[str]) -> dict[str, str]:
|
||||
"""Parse header strings in format 'Key: Value' into a dictionary."""
|
||||
headers = {}
|
||||
if not header_list:
|
||||
return headers
|
||||
|
||||
for header in header_list:
|
||||
if ":" in header:
|
||||
key, value = header.split(":", 1)
|
||||
headers[key.strip()] = value.strip()
|
||||
else:
|
||||
print(f"Warning: Ignoring malformed header: {header}")
|
||||
return headers
|
||||
|
||||
|
||||
def parse_env_vars(env_list: list[str]) -> dict[str, str]:
|
||||
"""Parse environment variable strings in format 'KEY=VALUE' into a dictionary."""
|
||||
env = {}
|
||||
if not env_list:
|
||||
return env
|
||||
|
||||
for env_var in env_list:
|
||||
if "=" in env_var:
|
||||
key, value = env_var.split("=", 1)
|
||||
env[key.strip()] = value.strip()
|
||||
else:
|
||||
print(f"Warning: Ignoring malformed environment variable: {env_var}")
|
||||
return env
|
||||
|
||||
|
||||
async def main():
|
||||
parser = argparse.ArgumentParser(
|
||||
description="Evaluate MCP servers using test questions",
|
||||
formatter_class=argparse.RawDescriptionHelpFormatter,
|
||||
epilog="""
|
||||
Examples:
|
||||
# Evaluate a local stdio MCP server
|
||||
python evaluation.py -t stdio -c python -a my_server.py eval.xml
|
||||
|
||||
# Evaluate an SSE MCP server
|
||||
python evaluation.py -t sse -u https://example.com/mcp -H "Authorization: Bearer token" eval.xml
|
||||
|
||||
# Evaluate an HTTP MCP server with custom model
|
||||
python evaluation.py -t http -u https://example.com/mcp -m claude-3-5-sonnet-20241022 eval.xml
|
||||
""",
|
||||
)
|
||||
|
||||
parser.add_argument("eval_file", type=Path, help="Path to evaluation XML file")
|
||||
parser.add_argument("-t", "--transport", choices=["stdio", "sse", "http"], default="stdio", help="Transport type (default: stdio)")
|
||||
parser.add_argument("-m", "--model", default="claude-3-7-sonnet-20250219", help="Claude model to use (default: claude-3-7-sonnet-20250219)")
|
||||
|
||||
stdio_group = parser.add_argument_group("stdio options")
|
||||
stdio_group.add_argument("-c", "--command", help="Command to run MCP server (stdio only)")
|
||||
stdio_group.add_argument("-a", "--args", nargs="+", help="Arguments for the command (stdio only)")
|
||||
stdio_group.add_argument("-e", "--env", nargs="+", help="Environment variables in KEY=VALUE format (stdio only)")
|
||||
|
||||
remote_group = parser.add_argument_group("sse/http options")
|
||||
remote_group.add_argument("-u", "--url", help="MCP server URL (sse/http only)")
|
||||
remote_group.add_argument("-H", "--header", nargs="+", dest="headers", help="HTTP headers in 'Key: Value' format (sse/http only)")
|
||||
|
||||
parser.add_argument("-o", "--output", type=Path, help="Output file for evaluation report (default: stdout)")
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
if not args.eval_file.exists():
|
||||
print(f"Error: Evaluation file not found: {args.eval_file}")
|
||||
sys.exit(1)
|
||||
|
||||
headers = parse_headers(args.headers) if args.headers else None
|
||||
env_vars = parse_env_vars(args.env) if args.env else None
|
||||
|
||||
try:
|
||||
connection = create_connection(
|
||||
transport=args.transport,
|
||||
command=args.command,
|
||||
args=args.args,
|
||||
env=env_vars,
|
||||
url=args.url,
|
||||
headers=headers,
|
||||
)
|
||||
except ValueError as e:
|
||||
print(f"Error: {e}")
|
||||
sys.exit(1)
|
||||
|
||||
print(f"🔗 Connecting to MCP server via {args.transport}...")
|
||||
|
||||
async with connection:
|
||||
print("✅ Connected successfully")
|
||||
report = await run_evaluation(args.eval_file, connection, args.model)
|
||||
|
||||
if args.output:
|
||||
args.output.write_text(report)
|
||||
print(f"\n✅ Report saved to {args.output}")
|
||||
else:
|
||||
print("\n" + report)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
@@ -0,0 +1,22 @@
|
||||
<evaluation>
|
||||
<qa_pair>
|
||||
<question>Calculate the compound interest on $10,000 invested at 5% annual interest rate, compounded monthly for 3 years. What is the final amount in dollars (rounded to 2 decimal places)?</question>
|
||||
<answer>11614.72</answer>
|
||||
</qa_pair>
|
||||
<qa_pair>
|
||||
<question>A projectile is launched at a 45-degree angle with an initial velocity of 50 m/s. Calculate the total distance (in meters) it has traveled from the launch point after 2 seconds, assuming g=9.8 m/s². Round to 2 decimal places.</question>
|
||||
<answer>87.25</answer>
|
||||
</qa_pair>
|
||||
<qa_pair>
|
||||
<question>A sphere has a volume of 500 cubic meters. Calculate its surface area in square meters. Round to 2 decimal places.</question>
|
||||
<answer>304.65</answer>
|
||||
</qa_pair>
|
||||
<qa_pair>
|
||||
<question>Calculate the population standard deviation of this dataset: [12, 15, 18, 22, 25, 30, 35]. Round to 2 decimal places.</question>
|
||||
<answer>7.61</answer>
|
||||
</qa_pair>
|
||||
<qa_pair>
|
||||
<question>Calculate the pH of a solution with a hydrogen ion concentration of 3.5 × 10^-5 M. Round to 2 decimal places.</question>
|
||||
<answer>4.46</answer>
|
||||
</qa_pair>
|
||||
</evaluation>
|
||||
@@ -0,0 +1,2 @@
|
||||
anthropic>=0.39.0
|
||||
mcp>=1.1.0
|
||||
@@ -0,0 +1,202 @@
|
||||
|
||||
Apache License
|
||||
Version 2.0, January 2004
|
||||
http://www.apache.org/licenses/
|
||||
|
||||
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
|
||||
|
||||
1. Definitions.
|
||||
|
||||
"License" shall mean the terms and conditions for use, reproduction,
|
||||
and distribution as defined by Sections 1 through 9 of this document.
|
||||
|
||||
"Licensor" shall mean the copyright owner or entity authorized by
|
||||
the copyright owner that is granting the License.
|
||||
|
||||
"Legal Entity" shall mean the union of the acting entity and all
|
||||
other entities that control, are controlled by, or are under common
|
||||
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|
||||
"control" means (i) the power, direct or indirect, to cause the
|
||||
direction or management of such entity, whether by contract or
|
||||
otherwise, or (ii) ownership of fifty percent (50%) or more of the
|
||||
outstanding shares, or (iii) beneficial ownership of such entity.
|
||||
|
||||
"You" (or "Your") shall mean an individual or Legal Entity
|
||||
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|
||||
|
||||
"Source" form shall mean the preferred form for making modifications,
|
||||
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|
||||
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|
||||
|
||||
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|
||||
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|
||||
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|
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|
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|
||||
"Work" shall mean the work of authorship, whether in Source or
|
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|
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|
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||||
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|
||||
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|
||||
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APPENDIX: How to apply the Apache License to your work.
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@@ -0,0 +1,356 @@
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---
|
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name: skill-creator
|
||||
description: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
|
||||
license: Complete terms in LICENSE.txt
|
||||
---
|
||||
|
||||
# Skill Creator
|
||||
|
||||
This skill provides guidance for creating effective skills.
|
||||
|
||||
## About Skills
|
||||
|
||||
Skills are modular, self-contained packages that extend Claude's capabilities by providing
|
||||
specialized knowledge, workflows, and tools. Think of them as "onboarding guides" for specific
|
||||
domains or tasks—they transform Claude from a general-purpose agent into a specialized agent
|
||||
equipped with procedural knowledge that no model can fully possess.
|
||||
|
||||
### What Skills Provide
|
||||
|
||||
1. Specialized workflows - Multi-step procedures for specific domains
|
||||
2. Tool integrations - Instructions for working with specific file formats or APIs
|
||||
3. Domain expertise - Company-specific knowledge, schemas, business logic
|
||||
4. Bundled resources - Scripts, references, and assets for complex and repetitive tasks
|
||||
|
||||
## Core Principles
|
||||
|
||||
### Concise is Key
|
||||
|
||||
The context window is a public good. Skills share the context window with everything else Claude needs: system prompt, conversation history, other Skills' metadata, and the actual user request.
|
||||
|
||||
**Default assumption: Claude is already very smart.** Only add context Claude doesn't already have. Challenge each piece of information: "Does Claude really need this explanation?" and "Does this paragraph justify its token cost?"
|
||||
|
||||
Prefer concise examples over verbose explanations.
|
||||
|
||||
### Set Appropriate Degrees of Freedom
|
||||
|
||||
Match the level of specificity to the task's fragility and variability:
|
||||
|
||||
**High freedom (text-based instructions)**: Use when multiple approaches are valid, decisions depend on context, or heuristics guide the approach.
|
||||
|
||||
**Medium freedom (pseudocode or scripts with parameters)**: Use when a preferred pattern exists, some variation is acceptable, or configuration affects behavior.
|
||||
|
||||
**Low freedom (specific scripts, few parameters)**: Use when operations are fragile and error-prone, consistency is critical, or a specific sequence must be followed.
|
||||
|
||||
Think of Claude as exploring a path: a narrow bridge with cliffs needs specific guardrails (low freedom), while an open field allows many routes (high freedom).
|
||||
|
||||
### Anatomy of a Skill
|
||||
|
||||
Every skill consists of a required SKILL.md file and optional bundled resources:
|
||||
|
||||
```
|
||||
skill-name/
|
||||
├── SKILL.md (required)
|
||||
│ ├── YAML frontmatter metadata (required)
|
||||
│ │ ├── name: (required)
|
||||
│ │ └── description: (required)
|
||||
│ └── Markdown instructions (required)
|
||||
└── Bundled Resources (optional)
|
||||
├── scripts/ - Executable code (Python/Bash/etc.)
|
||||
├── references/ - Documentation intended to be loaded into context as needed
|
||||
└── assets/ - Files used in output (templates, icons, fonts, etc.)
|
||||
```
|
||||
|
||||
#### SKILL.md (required)
|
||||
|
||||
Every SKILL.md consists of:
|
||||
|
||||
- **Frontmatter** (YAML): Contains `name` and `description` fields. These are the only fields that Claude reads to determine when the skill gets used, thus it is very important to be clear and comprehensive in describing what the skill is, and when it should be used.
|
||||
- **Body** (Markdown): Instructions and guidance for using the skill. Only loaded AFTER the skill triggers (if at all).
|
||||
|
||||
#### Bundled Resources (optional)
|
||||
|
||||
##### Scripts (`scripts/`)
|
||||
|
||||
Executable code (Python/Bash/etc.) for tasks that require deterministic reliability or are repeatedly rewritten.
|
||||
|
||||
- **When to include**: When the same code is being rewritten repeatedly or deterministic reliability is needed
|
||||
- **Example**: `scripts/rotate_pdf.py` for PDF rotation tasks
|
||||
- **Benefits**: Token efficient, deterministic, may be executed without loading into context
|
||||
- **Note**: Scripts may still need to be read by Claude for patching or environment-specific adjustments
|
||||
|
||||
##### References (`references/`)
|
||||
|
||||
Documentation and reference material intended to be loaded as needed into context to inform Claude's process and thinking.
|
||||
|
||||
- **When to include**: For documentation that Claude should reference while working
|
||||
- **Examples**: `references/finance.md` for financial schemas, `references/mnda.md` for company NDA template, `references/policies.md` for company policies, `references/api_docs.md` for API specifications
|
||||
- **Use cases**: Database schemas, API documentation, domain knowledge, company policies, detailed workflow guides
|
||||
- **Benefits**: Keeps SKILL.md lean, loaded only when Claude determines it's needed
|
||||
- **Best practice**: If files are large (>10k words), include grep search patterns in SKILL.md
|
||||
- **Avoid duplication**: Information should live in either SKILL.md or references files, not both. Prefer references files for detailed information unless it's truly core to the skill—this keeps SKILL.md lean while making information discoverable without hogging the context window. Keep only essential procedural instructions and workflow guidance in SKILL.md; move detailed reference material, schemas, and examples to references files.
|
||||
|
||||
##### Assets (`assets/`)
|
||||
|
||||
Files not intended to be loaded into context, but rather used within the output Claude produces.
|
||||
|
||||
- **When to include**: When the skill needs files that will be used in the final output
|
||||
- **Examples**: `assets/logo.png` for brand assets, `assets/slides.pptx` for PowerPoint templates, `assets/frontend-template/` for HTML/React boilerplate, `assets/font.ttf` for typography
|
||||
- **Use cases**: Templates, images, icons, boilerplate code, fonts, sample documents that get copied or modified
|
||||
- **Benefits**: Separates output resources from documentation, enables Claude to use files without loading them into context
|
||||
|
||||
#### What to Not Include in a Skill
|
||||
|
||||
A skill should only contain essential files that directly support its functionality. Do NOT create extraneous documentation or auxiliary files, including:
|
||||
|
||||
- README.md
|
||||
- INSTALLATION_GUIDE.md
|
||||
- QUICK_REFERENCE.md
|
||||
- CHANGELOG.md
|
||||
- etc.
|
||||
|
||||
The skill should only contain the information needed for an AI agent to do the job at hand. It should not contain auxilary context about the process that went into creating it, setup and testing procedures, user-facing documentation, etc. Creating additional documentation files just adds clutter and confusion.
|
||||
|
||||
### Progressive Disclosure Design Principle
|
||||
|
||||
Skills use a three-level loading system to manage context efficiently:
|
||||
|
||||
1. **Metadata (name + description)** - Always in context (~100 words)
|
||||
2. **SKILL.md body** - When skill triggers (<5k words)
|
||||
3. **Bundled resources** - As needed by Claude (Unlimited because scripts can be executed without reading into context window)
|
||||
|
||||
#### Progressive Disclosure Patterns
|
||||
|
||||
Keep SKILL.md body to the essentials and under 500 lines to minimize context bloat. Split content into separate files when approaching this limit. When splitting out content into other files, it is very important to reference them from SKILL.md and describe clearly when to read them, to ensure the reader of the skill knows they exist and when to use them.
|
||||
|
||||
**Key principle:** When a skill supports multiple variations, frameworks, or options, keep only the core workflow and selection guidance in SKILL.md. Move variant-specific details (patterns, examples, configuration) into separate reference files.
|
||||
|
||||
**Pattern 1: High-level guide with references**
|
||||
|
||||
```markdown
|
||||
# PDF Processing
|
||||
|
||||
## Quick start
|
||||
|
||||
Extract text with pdfplumber:
|
||||
[code example]
|
||||
|
||||
## Advanced features
|
||||
|
||||
- **Form filling**: See [FORMS.md](FORMS.md) for complete guide
|
||||
- **API reference**: See [REFERENCE.md](REFERENCE.md) for all methods
|
||||
- **Examples**: See [EXAMPLES.md](EXAMPLES.md) for common patterns
|
||||
```
|
||||
|
||||
Claude loads FORMS.md, REFERENCE.md, or EXAMPLES.md only when needed.
|
||||
|
||||
**Pattern 2: Domain-specific organization**
|
||||
|
||||
For Skills with multiple domains, organize content by domain to avoid loading irrelevant context:
|
||||
|
||||
```
|
||||
bigquery-skill/
|
||||
├── SKILL.md (overview and navigation)
|
||||
└── reference/
|
||||
├── finance.md (revenue, billing metrics)
|
||||
├── sales.md (opportunities, pipeline)
|
||||
├── product.md (API usage, features)
|
||||
└── marketing.md (campaigns, attribution)
|
||||
```
|
||||
|
||||
When a user asks about sales metrics, Claude only reads sales.md.
|
||||
|
||||
Similarly, for skills supporting multiple frameworks or variants, organize by variant:
|
||||
|
||||
```
|
||||
cloud-deploy/
|
||||
├── SKILL.md (workflow + provider selection)
|
||||
└── references/
|
||||
├── aws.md (AWS deployment patterns)
|
||||
├── gcp.md (GCP deployment patterns)
|
||||
└── azure.md (Azure deployment patterns)
|
||||
```
|
||||
|
||||
When the user chooses AWS, Claude only reads aws.md.
|
||||
|
||||
**Pattern 3: Conditional details**
|
||||
|
||||
Show basic content, link to advanced content:
|
||||
|
||||
```markdown
|
||||
# DOCX Processing
|
||||
|
||||
## Creating documents
|
||||
|
||||
Use docx-js for new documents. See [DOCX-JS.md](DOCX-JS.md).
|
||||
|
||||
## Editing documents
|
||||
|
||||
For simple edits, modify the XML directly.
|
||||
|
||||
**For tracked changes**: See [REDLINING.md](REDLINING.md)
|
||||
**For OOXML details**: See [OOXML.md](OOXML.md)
|
||||
```
|
||||
|
||||
Claude reads REDLINING.md or OOXML.md only when the user needs those features.
|
||||
|
||||
**Important guidelines:**
|
||||
|
||||
- **Avoid deeply nested references** - Keep references one level deep from SKILL.md. All reference files should link directly from SKILL.md.
|
||||
- **Structure longer reference files** - For files longer than 100 lines, include a table of contents at the top so Claude can see the full scope when previewing.
|
||||
|
||||
## Skill Creation Process
|
||||
|
||||
Skill creation involves these steps:
|
||||
|
||||
1. Understand the skill with concrete examples
|
||||
2. Plan reusable skill contents (scripts, references, assets)
|
||||
3. Initialize the skill (run init_skill.py)
|
||||
4. Edit the skill (implement resources and write SKILL.md)
|
||||
5. Package the skill (run package_skill.py)
|
||||
6. Iterate based on real usage
|
||||
|
||||
Follow these steps in order, skipping only if there is a clear reason why they are not applicable.
|
||||
|
||||
### Step 1: Understanding the Skill with Concrete Examples
|
||||
|
||||
Skip this step only when the skill's usage patterns are already clearly understood. It remains valuable even when working with an existing skill.
|
||||
|
||||
To create an effective skill, clearly understand concrete examples of how the skill will be used. This understanding can come from either direct user examples or generated examples that are validated with user feedback.
|
||||
|
||||
For example, when building an image-editor skill, relevant questions include:
|
||||
|
||||
- "What functionality should the image-editor skill support? Editing, rotating, anything else?"
|
||||
- "Can you give some examples of how this skill would be used?"
|
||||
- "I can imagine users asking for things like 'Remove the red-eye from this image' or 'Rotate this image'. Are there other ways you imagine this skill being used?"
|
||||
- "What would a user say that should trigger this skill?"
|
||||
|
||||
To avoid overwhelming users, avoid asking too many questions in a single message. Start with the most important questions and follow up as needed for better effectiveness.
|
||||
|
||||
Conclude this step when there is a clear sense of the functionality the skill should support.
|
||||
|
||||
### Step 2: Planning the Reusable Skill Contents
|
||||
|
||||
To turn concrete examples into an effective skill, analyze each example by:
|
||||
|
||||
1. Considering how to execute on the example from scratch
|
||||
2. Identifying what scripts, references, and assets would be helpful when executing these workflows repeatedly
|
||||
|
||||
Example: When building a `pdf-editor` skill to handle queries like "Help me rotate this PDF," the analysis shows:
|
||||
|
||||
1. Rotating a PDF requires re-writing the same code each time
|
||||
2. A `scripts/rotate_pdf.py` script would be helpful to store in the skill
|
||||
|
||||
Example: When designing a `frontend-webapp-builder` skill for queries like "Build me a todo app" or "Build me a dashboard to track my steps," the analysis shows:
|
||||
|
||||
1. Writing a frontend webapp requires the same boilerplate HTML/React each time
|
||||
2. An `assets/hello-world/` template containing the boilerplate HTML/React project files would be helpful to store in the skill
|
||||
|
||||
Example: When building a `big-query` skill to handle queries like "How many users have logged in today?" the analysis shows:
|
||||
|
||||
1. Querying BigQuery requires re-discovering the table schemas and relationships each time
|
||||
2. A `references/schema.md` file documenting the table schemas would be helpful to store in the skill
|
||||
|
||||
To establish the skill's contents, analyze each concrete example to create a list of the reusable resources to include: scripts, references, and assets.
|
||||
|
||||
### Step 3: Initializing the Skill
|
||||
|
||||
At this point, it is time to actually create the skill.
|
||||
|
||||
Skip this step only if the skill being developed already exists, and iteration or packaging is needed. In this case, continue to the next step.
|
||||
|
||||
When creating a new skill from scratch, always run the `init_skill.py` script. The script conveniently generates a new template skill directory that automatically includes everything a skill requires, making the skill creation process much more efficient and reliable.
|
||||
|
||||
Usage:
|
||||
|
||||
```bash
|
||||
scripts/init_skill.py <skill-name> --path <output-directory>
|
||||
```
|
||||
|
||||
The script:
|
||||
|
||||
- Creates the skill directory at the specified path
|
||||
- Generates a SKILL.md template with proper frontmatter and TODO placeholders
|
||||
- Creates example resource directories: `scripts/`, `references/`, and `assets/`
|
||||
- Adds example files in each directory that can be customized or deleted
|
||||
|
||||
After initialization, customize or remove the generated SKILL.md and example files as needed.
|
||||
|
||||
### Step 4: Edit the Skill
|
||||
|
||||
When editing the (newly-generated or existing) skill, remember that the skill is being created for another instance of Claude to use. Include information that would be beneficial and non-obvious to Claude. Consider what procedural knowledge, domain-specific details, or reusable assets would help another Claude instance execute these tasks more effectively.
|
||||
|
||||
#### Learn Proven Design Patterns
|
||||
|
||||
Consult these helpful guides based on your skill's needs:
|
||||
|
||||
- **Multi-step processes**: See references/workflows.md for sequential workflows and conditional logic
|
||||
- **Specific output formats or quality standards**: See references/output-patterns.md for template and example patterns
|
||||
|
||||
These files contain established best practices for effective skill design.
|
||||
|
||||
#### Start with Reusable Skill Contents
|
||||
|
||||
To begin implementation, start with the reusable resources identified above: `scripts/`, `references/`, and `assets/` files. Note that this step may require user input. For example, when implementing a `brand-guidelines` skill, the user may need to provide brand assets or templates to store in `assets/`, or documentation to store in `references/`.
|
||||
|
||||
Added scripts must be tested by actually running them to ensure there are no bugs and that the output matches what is expected. If there are many similar scripts, only a representative sample needs to be tested to ensure confidence that they all work while balancing time to completion.
|
||||
|
||||
Any example files and directories not needed for the skill should be deleted. The initialization script creates example files in `scripts/`, `references/`, and `assets/` to demonstrate structure, but most skills won't need all of them.
|
||||
|
||||
#### Update SKILL.md
|
||||
|
||||
**Writing Guidelines:** Always use imperative/infinitive form.
|
||||
|
||||
##### Frontmatter
|
||||
|
||||
Write the YAML frontmatter with `name` and `description`:
|
||||
|
||||
- `name`: The skill name
|
||||
- `description`: This is the primary triggering mechanism for your skill, and helps Claude understand when to use the skill.
|
||||
- Include both what the Skill does and specific triggers/contexts for when to use it.
|
||||
- Include all "when to use" information here - Not in the body. The body is only loaded after triggering, so "When to Use This Skill" sections in the body are not helpful to Claude.
|
||||
- Example description for a `docx` skill: "Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. Use when Claude needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks"
|
||||
|
||||
Do not include any other fields in YAML frontmatter.
|
||||
|
||||
##### Body
|
||||
|
||||
Write instructions for using the skill and its bundled resources.
|
||||
|
||||
### Step 5: Packaging a Skill
|
||||
|
||||
Once development of the skill is complete, it must be packaged into a distributable .skill file that gets shared with the user. The packaging process automatically validates the skill first to ensure it meets all requirements:
|
||||
|
||||
```bash
|
||||
scripts/package_skill.py <path/to/skill-folder>
|
||||
```
|
||||
|
||||
Optional output directory specification:
|
||||
|
||||
```bash
|
||||
scripts/package_skill.py <path/to/skill-folder> ./dist
|
||||
```
|
||||
|
||||
The packaging script will:
|
||||
|
||||
1. **Validate** the skill automatically, checking:
|
||||
|
||||
- YAML frontmatter format and required fields
|
||||
- Skill naming conventions and directory structure
|
||||
- Description completeness and quality
|
||||
- File organization and resource references
|
||||
|
||||
2. **Package** the skill if validation passes, creating a .skill file named after the skill (e.g., `my-skill.skill`) that includes all files and maintains the proper directory structure for distribution. The .skill file is a zip file with a .skill extension.
|
||||
|
||||
If validation fails, the script will report the errors and exit without creating a package. Fix any validation errors and run the packaging command again.
|
||||
|
||||
### Step 6: Iterate
|
||||
|
||||
After testing the skill, users may request improvements. Often this happens right after using the skill, with fresh context of how the skill performed.
|
||||
|
||||
**Iteration workflow:**
|
||||
|
||||
1. Use the skill on real tasks
|
||||
2. Notice struggles or inefficiencies
|
||||
3. Identify how SKILL.md or bundled resources should be updated
|
||||
4. Implement changes and test again
|
||||
@@ -0,0 +1,82 @@
|
||||
# Output Patterns
|
||||
|
||||
Use these patterns when skills need to produce consistent, high-quality output.
|
||||
|
||||
## Template Pattern
|
||||
|
||||
Provide templates for output format. Match the level of strictness to your needs.
|
||||
|
||||
**For strict requirements (like API responses or data formats):**
|
||||
|
||||
```markdown
|
||||
## Report structure
|
||||
|
||||
ALWAYS use this exact template structure:
|
||||
|
||||
# [Analysis Title]
|
||||
|
||||
## Executive summary
|
||||
[One-paragraph overview of key findings]
|
||||
|
||||
## Key findings
|
||||
- Finding 1 with supporting data
|
||||
- Finding 2 with supporting data
|
||||
- Finding 3 with supporting data
|
||||
|
||||
## Recommendations
|
||||
1. Specific actionable recommendation
|
||||
2. Specific actionable recommendation
|
||||
```
|
||||
|
||||
**For flexible guidance (when adaptation is useful):**
|
||||
|
||||
```markdown
|
||||
## Report structure
|
||||
|
||||
Here is a sensible default format, but use your best judgment:
|
||||
|
||||
# [Analysis Title]
|
||||
|
||||
## Executive summary
|
||||
[Overview]
|
||||
|
||||
## Key findings
|
||||
[Adapt sections based on what you discover]
|
||||
|
||||
## Recommendations
|
||||
[Tailor to the specific context]
|
||||
|
||||
Adjust sections as needed for the specific analysis type.
|
||||
```
|
||||
|
||||
## Examples Pattern
|
||||
|
||||
For skills where output quality depends on seeing examples, provide input/output pairs:
|
||||
|
||||
```markdown
|
||||
## Commit message format
|
||||
|
||||
Generate commit messages following these examples:
|
||||
|
||||
**Example 1:**
|
||||
Input: Added user authentication with JWT tokens
|
||||
Output:
|
||||
```
|
||||
feat(auth): implement JWT-based authentication
|
||||
|
||||
Add login endpoint and token validation middleware
|
||||
```
|
||||
|
||||
**Example 2:**
|
||||
Input: Fixed bug where dates displayed incorrectly in reports
|
||||
Output:
|
||||
```
|
||||
fix(reports): correct date formatting in timezone conversion
|
||||
|
||||
Use UTC timestamps consistently across report generation
|
||||
```
|
||||
|
||||
Follow this style: type(scope): brief description, then detailed explanation.
|
||||
```
|
||||
|
||||
Examples help Claude understand the desired style and level of detail more clearly than descriptions alone.
|
||||
@@ -0,0 +1,28 @@
|
||||
# Workflow Patterns
|
||||
|
||||
## Sequential Workflows
|
||||
|
||||
For complex tasks, break operations into clear, sequential steps. It is often helpful to give Claude an overview of the process towards the beginning of SKILL.md:
|
||||
|
||||
```markdown
|
||||
Filling a PDF form involves these steps:
|
||||
|
||||
1. Analyze the form (run analyze_form.py)
|
||||
2. Create field mapping (edit fields.json)
|
||||
3. Validate mapping (run validate_fields.py)
|
||||
4. Fill the form (run fill_form.py)
|
||||
5. Verify output (run verify_output.py)
|
||||
```
|
||||
|
||||
## Conditional Workflows
|
||||
|
||||
For tasks with branching logic, guide Claude through decision points:
|
||||
|
||||
```markdown
|
||||
1. Determine the modification type:
|
||||
**Creating new content?** → Follow "Creation workflow" below
|
||||
**Editing existing content?** → Follow "Editing workflow" below
|
||||
|
||||
2. Creation workflow: [steps]
|
||||
3. Editing workflow: [steps]
|
||||
```
|
||||
Executable
+303
@@ -0,0 +1,303 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Skill Initializer - Creates a new skill from template
|
||||
|
||||
Usage:
|
||||
init_skill.py <skill-name> --path <path>
|
||||
|
||||
Examples:
|
||||
init_skill.py my-new-skill --path skills/public
|
||||
init_skill.py my-api-helper --path skills/private
|
||||
init_skill.py custom-skill --path /custom/location
|
||||
"""
|
||||
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
|
||||
SKILL_TEMPLATE = """---
|
||||
name: {skill_name}
|
||||
description: [TODO: Complete and informative explanation of what the skill does and when to use it. Include WHEN to use this skill - specific scenarios, file types, or tasks that trigger it.]
|
||||
---
|
||||
|
||||
# {skill_title}
|
||||
|
||||
## Overview
|
||||
|
||||
[TODO: 1-2 sentences explaining what this skill enables]
|
||||
|
||||
## Structuring This Skill
|
||||
|
||||
[TODO: Choose the structure that best fits this skill's purpose. Common patterns:
|
||||
|
||||
**1. Workflow-Based** (best for sequential processes)
|
||||
- Works well when there are clear step-by-step procedures
|
||||
- Example: DOCX skill with "Workflow Decision Tree" → "Reading" → "Creating" → "Editing"
|
||||
- Structure: ## Overview → ## Workflow Decision Tree → ## Step 1 → ## Step 2...
|
||||
|
||||
**2. Task-Based** (best for tool collections)
|
||||
- Works well when the skill offers different operations/capabilities
|
||||
- Example: PDF skill with "Quick Start" → "Merge PDFs" → "Split PDFs" → "Extract Text"
|
||||
- Structure: ## Overview → ## Quick Start → ## Task Category 1 → ## Task Category 2...
|
||||
|
||||
**3. Reference/Guidelines** (best for standards or specifications)
|
||||
- Works well for brand guidelines, coding standards, or requirements
|
||||
- Example: Brand styling with "Brand Guidelines" → "Colors" → "Typography" → "Features"
|
||||
- Structure: ## Overview → ## Guidelines → ## Specifications → ## Usage...
|
||||
|
||||
**4. Capabilities-Based** (best for integrated systems)
|
||||
- Works well when the skill provides multiple interrelated features
|
||||
- Example: Product Management with "Core Capabilities" → numbered capability list
|
||||
- Structure: ## Overview → ## Core Capabilities → ### 1. Feature → ### 2. Feature...
|
||||
|
||||
Patterns can be mixed and matched as needed. Most skills combine patterns (e.g., start with task-based, add workflow for complex operations).
|
||||
|
||||
Delete this entire "Structuring This Skill" section when done - it's just guidance.]
|
||||
|
||||
## [TODO: Replace with the first main section based on chosen structure]
|
||||
|
||||
[TODO: Add content here. See examples in existing skills:
|
||||
- Code samples for technical skills
|
||||
- Decision trees for complex workflows
|
||||
- Concrete examples with realistic user requests
|
||||
- References to scripts/templates/references as needed]
|
||||
|
||||
## Resources
|
||||
|
||||
This skill includes example resource directories that demonstrate how to organize different types of bundled resources:
|
||||
|
||||
### scripts/
|
||||
Executable code (Python/Bash/etc.) that can be run directly to perform specific operations.
|
||||
|
||||
**Examples from other skills:**
|
||||
- PDF skill: `fill_fillable_fields.py`, `extract_form_field_info.py` - utilities for PDF manipulation
|
||||
- DOCX skill: `document.py`, `utilities.py` - Python modules for document processing
|
||||
|
||||
**Appropriate for:** Python scripts, shell scripts, or any executable code that performs automation, data processing, or specific operations.
|
||||
|
||||
**Note:** Scripts may be executed without loading into context, but can still be read by Claude for patching or environment adjustments.
|
||||
|
||||
### references/
|
||||
Documentation and reference material intended to be loaded into context to inform Claude's process and thinking.
|
||||
|
||||
**Examples from other skills:**
|
||||
- Product management: `communication.md`, `context_building.md` - detailed workflow guides
|
||||
- BigQuery: API reference documentation and query examples
|
||||
- Finance: Schema documentation, company policies
|
||||
|
||||
**Appropriate for:** In-depth documentation, API references, database schemas, comprehensive guides, or any detailed information that Claude should reference while working.
|
||||
|
||||
### assets/
|
||||
Files not intended to be loaded into context, but rather used within the output Claude produces.
|
||||
|
||||
**Examples from other skills:**
|
||||
- Brand styling: PowerPoint template files (.pptx), logo files
|
||||
- Frontend builder: HTML/React boilerplate project directories
|
||||
- Typography: Font files (.ttf, .woff2)
|
||||
|
||||
**Appropriate for:** Templates, boilerplate code, document templates, images, icons, fonts, or any files meant to be copied or used in the final output.
|
||||
|
||||
---
|
||||
|
||||
**Any unneeded directories can be deleted.** Not every skill requires all three types of resources.
|
||||
"""
|
||||
|
||||
EXAMPLE_SCRIPT = '''#!/usr/bin/env python3
|
||||
"""
|
||||
Example helper script for {skill_name}
|
||||
|
||||
This is a placeholder script that can be executed directly.
|
||||
Replace with actual implementation or delete if not needed.
|
||||
|
||||
Example real scripts from other skills:
|
||||
- pdf/scripts/fill_fillable_fields.py - Fills PDF form fields
|
||||
- pdf/scripts/convert_pdf_to_images.py - Converts PDF pages to images
|
||||
"""
|
||||
|
||||
def main():
|
||||
print("This is an example script for {skill_name}")
|
||||
# TODO: Add actual script logic here
|
||||
# This could be data processing, file conversion, API calls, etc.
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
'''
|
||||
|
||||
EXAMPLE_REFERENCE = """# Reference Documentation for {skill_title}
|
||||
|
||||
This is a placeholder for detailed reference documentation.
|
||||
Replace with actual reference content or delete if not needed.
|
||||
|
||||
Example real reference docs from other skills:
|
||||
- product-management/references/communication.md - Comprehensive guide for status updates
|
||||
- product-management/references/context_building.md - Deep-dive on gathering context
|
||||
- bigquery/references/ - API references and query examples
|
||||
|
||||
## When Reference Docs Are Useful
|
||||
|
||||
Reference docs are ideal for:
|
||||
- Comprehensive API documentation
|
||||
- Detailed workflow guides
|
||||
- Complex multi-step processes
|
||||
- Information too lengthy for main SKILL.md
|
||||
- Content that's only needed for specific use cases
|
||||
|
||||
## Structure Suggestions
|
||||
|
||||
### API Reference Example
|
||||
- Overview
|
||||
- Authentication
|
||||
- Endpoints with examples
|
||||
- Error codes
|
||||
- Rate limits
|
||||
|
||||
### Workflow Guide Example
|
||||
- Prerequisites
|
||||
- Step-by-step instructions
|
||||
- Common patterns
|
||||
- Troubleshooting
|
||||
- Best practices
|
||||
"""
|
||||
|
||||
EXAMPLE_ASSET = """# Example Asset File
|
||||
|
||||
This placeholder represents where asset files would be stored.
|
||||
Replace with actual asset files (templates, images, fonts, etc.) or delete if not needed.
|
||||
|
||||
Asset files are NOT intended to be loaded into context, but rather used within
|
||||
the output Claude produces.
|
||||
|
||||
Example asset files from other skills:
|
||||
- Brand guidelines: logo.png, slides_template.pptx
|
||||
- Frontend builder: hello-world/ directory with HTML/React boilerplate
|
||||
- Typography: custom-font.ttf, font-family.woff2
|
||||
- Data: sample_data.csv, test_dataset.json
|
||||
|
||||
## Common Asset Types
|
||||
|
||||
- Templates: .pptx, .docx, boilerplate directories
|
||||
- Images: .png, .jpg, .svg, .gif
|
||||
- Fonts: .ttf, .otf, .woff, .woff2
|
||||
- Boilerplate code: Project directories, starter files
|
||||
- Icons: .ico, .svg
|
||||
- Data files: .csv, .json, .xml, .yaml
|
||||
|
||||
Note: This is a text placeholder. Actual assets can be any file type.
|
||||
"""
|
||||
|
||||
|
||||
def title_case_skill_name(skill_name):
|
||||
"""Convert hyphenated skill name to Title Case for display."""
|
||||
return ' '.join(word.capitalize() for word in skill_name.split('-'))
|
||||
|
||||
|
||||
def init_skill(skill_name, path):
|
||||
"""
|
||||
Initialize a new skill directory with template SKILL.md.
|
||||
|
||||
Args:
|
||||
skill_name: Name of the skill
|
||||
path: Path where the skill directory should be created
|
||||
|
||||
Returns:
|
||||
Path to created skill directory, or None if error
|
||||
"""
|
||||
# Determine skill directory path
|
||||
skill_dir = Path(path).resolve() / skill_name
|
||||
|
||||
# Check if directory already exists
|
||||
if skill_dir.exists():
|
||||
print(f"❌ Error: Skill directory already exists: {skill_dir}")
|
||||
return None
|
||||
|
||||
# Create skill directory
|
||||
try:
|
||||
skill_dir.mkdir(parents=True, exist_ok=False)
|
||||
print(f"✅ Created skill directory: {skill_dir}")
|
||||
except Exception as e:
|
||||
print(f"❌ Error creating directory: {e}")
|
||||
return None
|
||||
|
||||
# Create SKILL.md from template
|
||||
skill_title = title_case_skill_name(skill_name)
|
||||
skill_content = SKILL_TEMPLATE.format(
|
||||
skill_name=skill_name,
|
||||
skill_title=skill_title
|
||||
)
|
||||
|
||||
skill_md_path = skill_dir / 'SKILL.md'
|
||||
try:
|
||||
skill_md_path.write_text(skill_content)
|
||||
print("✅ Created SKILL.md")
|
||||
except Exception as e:
|
||||
print(f"❌ Error creating SKILL.md: {e}")
|
||||
return None
|
||||
|
||||
# Create resource directories with example files
|
||||
try:
|
||||
# Create scripts/ directory with example script
|
||||
scripts_dir = skill_dir / 'scripts'
|
||||
scripts_dir.mkdir(exist_ok=True)
|
||||
example_script = scripts_dir / 'example.py'
|
||||
example_script.write_text(EXAMPLE_SCRIPT.format(skill_name=skill_name))
|
||||
example_script.chmod(0o755)
|
||||
print("✅ Created scripts/example.py")
|
||||
|
||||
# Create references/ directory with example reference doc
|
||||
references_dir = skill_dir / 'references'
|
||||
references_dir.mkdir(exist_ok=True)
|
||||
example_reference = references_dir / 'api_reference.md'
|
||||
example_reference.write_text(EXAMPLE_REFERENCE.format(skill_title=skill_title))
|
||||
print("✅ Created references/api_reference.md")
|
||||
|
||||
# Create assets/ directory with example asset placeholder
|
||||
assets_dir = skill_dir / 'assets'
|
||||
assets_dir.mkdir(exist_ok=True)
|
||||
example_asset = assets_dir / 'example_asset.txt'
|
||||
example_asset.write_text(EXAMPLE_ASSET)
|
||||
print("✅ Created assets/example_asset.txt")
|
||||
except Exception as e:
|
||||
print(f"❌ Error creating resource directories: {e}")
|
||||
return None
|
||||
|
||||
# Print next steps
|
||||
print(f"\n✅ Skill '{skill_name}' initialized successfully at {skill_dir}")
|
||||
print("\nNext steps:")
|
||||
print("1. Edit SKILL.md to complete the TODO items and update the description")
|
||||
print("2. Customize or delete the example files in scripts/, references/, and assets/")
|
||||
print("3. Run the validator when ready to check the skill structure")
|
||||
|
||||
return skill_dir
|
||||
|
||||
|
||||
def main():
|
||||
if len(sys.argv) < 4 or sys.argv[2] != '--path':
|
||||
print("Usage: init_skill.py <skill-name> --path <path>")
|
||||
print("\nSkill name requirements:")
|
||||
print(" - Hyphen-case identifier (e.g., 'data-analyzer')")
|
||||
print(" - Lowercase letters, digits, and hyphens only")
|
||||
print(" - Max 40 characters")
|
||||
print(" - Must match directory name exactly")
|
||||
print("\nExamples:")
|
||||
print(" init_skill.py my-new-skill --path skills/public")
|
||||
print(" init_skill.py my-api-helper --path skills/private")
|
||||
print(" init_skill.py custom-skill --path /custom/location")
|
||||
sys.exit(1)
|
||||
|
||||
skill_name = sys.argv[1]
|
||||
path = sys.argv[3]
|
||||
|
||||
print(f"🚀 Initializing skill: {skill_name}")
|
||||
print(f" Location: {path}")
|
||||
print()
|
||||
|
||||
result = init_skill(skill_name, path)
|
||||
|
||||
if result:
|
||||
sys.exit(0)
|
||||
else:
|
||||
sys.exit(1)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
+110
@@ -0,0 +1,110 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Skill Packager - Creates a distributable .skill file of a skill folder
|
||||
|
||||
Usage:
|
||||
python utils/package_skill.py <path/to/skill-folder> [output-directory]
|
||||
|
||||
Example:
|
||||
python utils/package_skill.py skills/public/my-skill
|
||||
python utils/package_skill.py skills/public/my-skill ./dist
|
||||
"""
|
||||
|
||||
import sys
|
||||
import zipfile
|
||||
from pathlib import Path
|
||||
from quick_validate import validate_skill
|
||||
|
||||
|
||||
def package_skill(skill_path, output_dir=None):
|
||||
"""
|
||||
Package a skill folder into a .skill file.
|
||||
|
||||
Args:
|
||||
skill_path: Path to the skill folder
|
||||
output_dir: Optional output directory for the .skill file (defaults to current directory)
|
||||
|
||||
Returns:
|
||||
Path to the created .skill file, or None if error
|
||||
"""
|
||||
skill_path = Path(skill_path).resolve()
|
||||
|
||||
# Validate skill folder exists
|
||||
if not skill_path.exists():
|
||||
print(f"❌ Error: Skill folder not found: {skill_path}")
|
||||
return None
|
||||
|
||||
if not skill_path.is_dir():
|
||||
print(f"❌ Error: Path is not a directory: {skill_path}")
|
||||
return None
|
||||
|
||||
# Validate SKILL.md exists
|
||||
skill_md = skill_path / "SKILL.md"
|
||||
if not skill_md.exists():
|
||||
print(f"❌ Error: SKILL.md not found in {skill_path}")
|
||||
return None
|
||||
|
||||
# Run validation before packaging
|
||||
print("🔍 Validating skill...")
|
||||
valid, message = validate_skill(skill_path)
|
||||
if not valid:
|
||||
print(f"❌ Validation failed: {message}")
|
||||
print(" Please fix the validation errors before packaging.")
|
||||
return None
|
||||
print(f"✅ {message}\n")
|
||||
|
||||
# Determine output location
|
||||
skill_name = skill_path.name
|
||||
if output_dir:
|
||||
output_path = Path(output_dir).resolve()
|
||||
output_path.mkdir(parents=True, exist_ok=True)
|
||||
else:
|
||||
output_path = Path.cwd()
|
||||
|
||||
skill_filename = output_path / f"{skill_name}.skill"
|
||||
|
||||
# Create the .skill file (zip format)
|
||||
try:
|
||||
with zipfile.ZipFile(skill_filename, 'w', zipfile.ZIP_DEFLATED) as zipf:
|
||||
# Walk through the skill directory
|
||||
for file_path in skill_path.rglob('*'):
|
||||
if file_path.is_file():
|
||||
# Calculate the relative path within the zip
|
||||
arcname = file_path.relative_to(skill_path.parent)
|
||||
zipf.write(file_path, arcname)
|
||||
print(f" Added: {arcname}")
|
||||
|
||||
print(f"\n✅ Successfully packaged skill to: {skill_filename}")
|
||||
return skill_filename
|
||||
|
||||
except Exception as e:
|
||||
print(f"❌ Error creating .skill file: {e}")
|
||||
return None
|
||||
|
||||
|
||||
def main():
|
||||
if len(sys.argv) < 2:
|
||||
print("Usage: python utils/package_skill.py <path/to/skill-folder> [output-directory]")
|
||||
print("\nExample:")
|
||||
print(" python utils/package_skill.py skills/public/my-skill")
|
||||
print(" python utils/package_skill.py skills/public/my-skill ./dist")
|
||||
sys.exit(1)
|
||||
|
||||
skill_path = sys.argv[1]
|
||||
output_dir = sys.argv[2] if len(sys.argv) > 2 else None
|
||||
|
||||
print(f"📦 Packaging skill: {skill_path}")
|
||||
if output_dir:
|
||||
print(f" Output directory: {output_dir}")
|
||||
print()
|
||||
|
||||
result = package_skill(skill_path, output_dir)
|
||||
|
||||
if result:
|
||||
sys.exit(0)
|
||||
else:
|
||||
sys.exit(1)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
+95
@@ -0,0 +1,95 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Quick validation script for skills - minimal version
|
||||
"""
|
||||
|
||||
import sys
|
||||
import os
|
||||
import re
|
||||
import yaml
|
||||
from pathlib import Path
|
||||
|
||||
def validate_skill(skill_path):
|
||||
"""Basic validation of a skill"""
|
||||
skill_path = Path(skill_path)
|
||||
|
||||
# Check SKILL.md exists
|
||||
skill_md = skill_path / 'SKILL.md'
|
||||
if not skill_md.exists():
|
||||
return False, "SKILL.md not found"
|
||||
|
||||
# Read and validate frontmatter
|
||||
content = skill_md.read_text()
|
||||
if not content.startswith('---'):
|
||||
return False, "No YAML frontmatter found"
|
||||
|
||||
# Extract frontmatter
|
||||
match = re.match(r'^---\n(.*?)\n---', content, re.DOTALL)
|
||||
if not match:
|
||||
return False, "Invalid frontmatter format"
|
||||
|
||||
frontmatter_text = match.group(1)
|
||||
|
||||
# Parse YAML frontmatter
|
||||
try:
|
||||
frontmatter = yaml.safe_load(frontmatter_text)
|
||||
if not isinstance(frontmatter, dict):
|
||||
return False, "Frontmatter must be a YAML dictionary"
|
||||
except yaml.YAMLError as e:
|
||||
return False, f"Invalid YAML in frontmatter: {e}"
|
||||
|
||||
# Define allowed properties
|
||||
ALLOWED_PROPERTIES = {'name', 'description', 'license', 'allowed-tools', 'metadata'}
|
||||
|
||||
# Check for unexpected properties (excluding nested keys under metadata)
|
||||
unexpected_keys = set(frontmatter.keys()) - ALLOWED_PROPERTIES
|
||||
if unexpected_keys:
|
||||
return False, (
|
||||
f"Unexpected key(s) in SKILL.md frontmatter: {', '.join(sorted(unexpected_keys))}. "
|
||||
f"Allowed properties are: {', '.join(sorted(ALLOWED_PROPERTIES))}"
|
||||
)
|
||||
|
||||
# Check required fields
|
||||
if 'name' not in frontmatter:
|
||||
return False, "Missing 'name' in frontmatter"
|
||||
if 'description' not in frontmatter:
|
||||
return False, "Missing 'description' in frontmatter"
|
||||
|
||||
# Extract name for validation
|
||||
name = frontmatter.get('name', '')
|
||||
if not isinstance(name, str):
|
||||
return False, f"Name must be a string, got {type(name).__name__}"
|
||||
name = name.strip()
|
||||
if name:
|
||||
# Check naming convention (hyphen-case: lowercase with hyphens)
|
||||
if not re.match(r'^[a-z0-9-]+$', name):
|
||||
return False, f"Name '{name}' should be hyphen-case (lowercase letters, digits, and hyphens only)"
|
||||
if name.startswith('-') or name.endswith('-') or '--' in name:
|
||||
return False, f"Name '{name}' cannot start/end with hyphen or contain consecutive hyphens"
|
||||
# Check name length (max 64 characters per spec)
|
||||
if len(name) > 64:
|
||||
return False, f"Name is too long ({len(name)} characters). Maximum is 64 characters."
|
||||
|
||||
# Extract and validate description
|
||||
description = frontmatter.get('description', '')
|
||||
if not isinstance(description, str):
|
||||
return False, f"Description must be a string, got {type(description).__name__}"
|
||||
description = description.strip()
|
||||
if description:
|
||||
# Check for angle brackets
|
||||
if '<' in description or '>' in description:
|
||||
return False, "Description cannot contain angle brackets (< or >)"
|
||||
# Check description length (max 1024 characters per spec)
|
||||
if len(description) > 1024:
|
||||
return False, f"Description is too long ({len(description)} characters). Maximum is 1024 characters."
|
||||
|
||||
return True, "Skill is valid!"
|
||||
|
||||
if __name__ == "__main__":
|
||||
if len(sys.argv) != 2:
|
||||
print("Usage: python quick_validate.py <skill_directory>")
|
||||
sys.exit(1)
|
||||
|
||||
valid, message = validate_skill(sys.argv[1])
|
||||
print(message)
|
||||
sys.exit(0 if valid else 1)
|
||||
@@ -0,0 +1,3 @@
|
||||
# Agent Skills Spec
|
||||
|
||||
The spec is now located at <https://agentskills.io/specification>
|
||||
@@ -0,0 +1,6 @@
|
||||
---
|
||||
name: template-skill
|
||||
description: Replace with description of the skill and when Claude should use it.
|
||||
---
|
||||
|
||||
# Insert instructions below
|
||||
Reference in New Issue
Block a user