NCBI Literature Search MCP Server

# Development Notes ## Session: 2025-06-27 - Analytics Implementation ### What We Accomplished 1. **Analytics System Integration** - Successfully integrated comprehensive analytics tracking - Added performance monitoring and usage pattern analysis - Implemented persistent storage with periodic flushing - Created MCP tools for analytics access 2. **Testing & Validation** - Created and ran comprehensive functionality tests - Verified NCBI search capabilities remain unchanged - Validated analytics tracking works correctly - Confirmed server startup and shutdown processes 3. **Bug Fixes** - Resolved `analytics_manager` global declaration syntax errors - Fixed import issues with unused `SimpleLRUCache` - Ensured proper module imports and dependencies 4. **Git Workflow** - Successfully used GitHub CLI for pull request creation - Merged feature branch via GitHub web interface - Applied post-merge fixes directly to main branch - Cleaned up feature branch after confirming identical content ### Technical Insights #### Server Architecture - MCP server uses FastMCP framework - Analytics integrated via decorators on MCP tools - Caching system supports both Redis and file-based fallback - Batch processing capabilities for efficient bulk operations #### Development Setup - Poetry for dependency management - Module structure requires running as `python -m src.ncbi_mcp_server.server` - Environment variables supported via `.env` files - Comprehensive testing can be done with custom test scripts #### Key Files Modified - `src/ncbi_mcp_server/server.py` - Main server with analytics integration - `src/ncbi_mcp_server/analytics.py` - Analytics tracking system - `README.md` - Updated with analytics documentation - `TODO.md` - Project status and next steps ### Lessons Learned 1. **Global Variable Management**: Be careful with global declarations in Python - they must come before usage 2. **Import Dependencies**: Remove unused imports to avoid import errors 3. **Module Testing**: Create isolated test scripts to verify functionality without full MCP setup 4. **Git Branch Management**: Force delete (`-D`) may be needed when commit history diverges after merge ### Next Development Session Priorities 1. **Production Setup**: Create proper environment configuration templates 2. **Docker Validation**: Test and verify containerized deployment 3. **Performance Tuning**: Use analytics data to optimize cache and rate limiting 4. **Health Monitoring**: Implement proper health check endpoints ### Quick Commands for Reference ```bash # Run server for testing poetry run python -m src.ncbi_mcp_server.server # Test functionality poetry run python test_functionality.py # Git branch cleanup git branch -D branch_name git push origin --delete branch_name # Create pull request via CLI gh pr create --title "Title" --body "Description" ``` ### Current Status ✅ **Project is stable and fully functional** ✅ **Analytics system is working correctly** ✅ **All original NCBI functionality preserved** ✅ **Ready for production deployment considerations** --- *Last updated: 2025-06-27*