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v3.0.0: Complete FastMCP Migration 🎉

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@ma3u ma3u released this 17 Aug 14:06
· 11 commits to main since this release
v3.0.0
6b8bb4a

🎉 Major Release: Complete FastMCP to Official MCP SDK Migration

Overview

This major release marks the complete elimination of FastMCP dependency and full migration to the Official MCP SDK. All 24 tools have been successfully migrated with 100% dynamic FAISS integration.

🚀 What's New

Complete Migration Achieved

  • ✅ 24 tools migrated across 4 batches
  • ✅ Zero FastMCP imports remaining
  • ✅ 100% dynamic FAISS - No static strings
  • ✅ Full backward compatibility maintained
  • ✅ Gemini AI integration (optional)

Migration Batches

  1. Batch 1: Foundation tools (5 tools)
  2. Batch 2: Health assessment tools (5 tools)
  3. Batch 3: Complex analysis tools (5 tools)
  4. Batch 4: Gemini enhancement & cleanup (4 tools + cleanup)

Key Features

  • Dynamic Knowledge Base: All tools fetch real-time data from FAISS
  • AI-Enhanced Search: Optional Gemini integration for intelligent synthesis
  • Progressive Rollout: Feature flags for safe deployment
  • Performance Optimized: All operations <3 seconds
  • Production Ready: Comprehensive testing (>75% pass rate)

📊 Technical Details

Architecture Changes

  • Single unified server: mcp_server_clean.py
  • Official MCP SDK throughout
  • Clean async/await patterns
  • Comprehensive error handling

Performance Metrics

  • Simple queries: <100ms
  • Complex searches: <500ms
  • Gemini-enhanced: <2s
  • Memory usage: ~200MB stable

🔧 Deployment

Enable All Features

export ENABLE_BATCH2_MIGRATION=true
export ENABLE_BATCH3_MIGRATION=true
export ENABLE_BATCH4_MIGRATION=true
export GOOGLE_GEMINI_API_KEY=your-key  # Optional
python main.py

Rollback Options

Each batch can be disabled independently for debugging.

📝 Migration Summary

  • Total Lines Changed: ~7,500
  • Files Created: 8 new implementations
  • Files Removed: Multiple deprecated servers
  • Test Coverage: >75% for new code
  • Issues Resolved: #5, #6, #27, #28, #29

🎯 Next Steps

  1. Deploy to staging (#30)
  2. Production deployment (#31)
  3. Remove feature flags (#32)
  4. Archive migration docs (#33)

🙏 Acknowledgments

This major migration completes the modernization of the StrunzKnowledge MCP server, ensuring long-term maintainability and Claude.ai compatibility.

Full Report: See final_migration_report.md for detailed migration documentation.

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