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Phase 2e: Claude.ai Integration Validation & Cleanup (Day 14) #24

@ma3u

Description

@ma3u

🎯 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.py references
  • Update railway-deploy.py to use mcp_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

  1. Final code review
  2. Update version to 0.9.0
  3. Create release with migration summary
  4. Deploy to Railway
  5. 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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