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enhancementNew feature or requestNew feature or requestphase: 2-implementationPhase 2 - Implementation workPhase 2 - Implementation workpriority: highHigh priority workHigh priority work
Description
🎯 Objective
Complete FastMCP elimination, remove legacy code, and validate Claude.ai connectivity restoration.
📋 Final Tasks
- Remove
unified_mcp_server.py(FastMCP-based) - Remove
enhanced_server.pyreferences - Update
railway-deploy.pyto usemcp_sdk_clean.py - Clean up FastMCP dependencies from requirements.txt
- Update all documentation
- Final performance report
🧪 Claude.ai Validation
- Test connection from Claude.ai web interface
- Verify "Connected" status (not "Disabled")
- Test all 20 tools via Claude.ai
- Validate OAuth flow if required
- Document any remaining issues
📊 Performance Comparison Report
Generate comprehensive report including:
- Tool-by-tool performance comparison
- Overall performance impact analysis
- Memory usage comparison
- Response time distribution
- Recommendations for further optimization
✅ Success Criteria
- Claude.ai shows "Connected" status ✅
- All 20 tools functional via Claude.ai
- No FastMCP dependencies remain
- Performance within acceptable bounds
- Production deployment successful
- Documentation fully updated
🚀 Deployment Steps
- Final code review
- Update version to 0.9.0
- Create release with migration summary
- Deploy to Railway
- Monitor for 24 hours
📅 Timeline
- Day 14: Cleanup, validation, and production deployment
Depends on: All batch migrations (#20, #21, #22, #23)
Delivers: Fully functional Claude.ai integration
🎉 Expected Outcome
StrunzKnowledge MCP server fully compatible with Claude.ai, using Official MCP SDK exclusively.
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enhancementNew feature or requestNew feature or requestphase: 2-implementationPhase 2 - Implementation workPhase 2 - Implementation workpriority: highHigh priority workHigh priority work