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Bilal Muhammad Khan
a038d87bca
Completed Phase III AI chatbot backend infrastructure with stateless MCP server exposing task management tools for OpenAI Agents SDK integration. Updated constitution with timeless AI/external service integration principles applicable across all project phases. MCP Server Implementation: - 5 stateless tools (add_task, list_tasks, complete_task, delete_task, update_task) - User-scoped operations with UUID user_id enforcement - Soft delete pattern with deleted_at timestamps - Structured JSON responses optimized for AI interpretation - Comprehensive error handling with actionable messages - Database state persistence (zero in-memory state) - SSE over HTTP transport for production deployment - Structured logging for observability (tool_name, user_id, duration) Constitutional Updates: - Section 11: AI & External Service Integration Principles - LLM service integration patterns (SDKs, streaming, rate limiting) - External tool protocol architecture (stateless, scoped, idempotent) - Conversational state management (database persistence, resumption) - AI tool design standards (atomic operations, structured responses) - Conversational interface security (domain allowlist, httpOnly cookies) Specification Artifacts: - spec.md: 5 user scenarios with acceptance criteria (P1-P3 priorities) - plan.md: 4-layer architecture (protocol, tool, business, data) - tasks.md: 29 implementation tasks across 8 categories (100% complete) - data-model.md: Database schema with soft delete support - research.md: MCP SDK patterns and integration analysis Documentation: - 10 PHRs documenting spec/plan/task/implementation workflow - Phase 3 planning artifacts and requirements - README with MCP server setup and testing instructions Fixes #007-mcp-server Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>