Portable MCP Toolkit

# MCP Toolkit Test Results ## Prerequisites Check ✅ - ✅ **Server Script**: `mcp_intelligence_server.py` exists and is executable - ✅ **Python Environment**: Virtual environment created and dependencies installed - ✅ **Ollama**: Running with required models: - `qwen3:8b` ✅ - `phi4:14b` ✅ - `mxbai-embed-large` ✅ - ✅ **Qdrant**: Running on http://localhost:6333 - ✅ **Workspace**: C:\AIStack exists with Python files ## Configuration ✅ - ✅ **MCP Settings**: `.cursor/mcp_settings.json` configured with: - filesystem (uses `${workspaceFolder}`) - git (uses `${workspaceFolder}`) - github (token configured) - code-intelligence (points to server script) ## Testing Instructions ### Step 1: Verify MCP Settings in Cursor 1. Check if MCP settings are in Cursor config: ```powershell Test-Path "$env:APPDATA\Cursor\User\mcp_settings.json" ``` 2. If not present, copy them: ```powershell Copy-Item C:\AIStack-MCP\.cursor\mcp_settings.json "$env:APPDATA\Cursor\User\mcp_settings.json" ``` ### Step 2: Open Project in Cursor ```powershell cd C:\AIStack cursor . ``` ### Step 3: Test in Cursor Chat **Test 1: Index Workspace** ``` Use code-intelligence to index_workspace with file_extensions .py,.js,.ts and max_files 100 ``` Expected: Should start indexing files and return summary like "✓ Indexed X files with Y chunks" **Test 2: Semantic Search** ``` Use code-intelligence to semantic_search for query 'error handling' with max_results 5 ``` Expected: Should return relevant code snippets from C:\AIStack **Test 3: Pattern Analysis** ``` Use code-intelligence to analyze_patterns for pattern_type 'async' with max_examples 3 ``` Expected: Should analyze async patterns in the codebase ## Troubleshooting ### If MCP servers don't appear: 1. **Check Cursor logs**: Help > Toggle Developer Tools > Console 2. **Verify Python path**: The server uses `python` command - ensure it's in PATH 3. **Check server path**: Verify `C:\AIStack-MCP\mcp_intelligence_server.py` exists ### If indexing fails: - Check Qdrant is running: `curl http://localhost:6333/collections` - Check Ollama is running: `ollama list` - Verify workspace path is correct ### If search returns "not indexed": - Run `index_workspace` first - Check Qdrant collection was created - Verify files match the extensions specified ## Next Steps After successful testing: 1. ✅ Index your main projects 2. ✅ Use semantic search for code discovery 3. ✅ Use pattern analysis to understand codebase 4. ✅ Use code generation for new features ## Notes - The server uses `qwen3:8b` (updated from qwen2.5:8b) - Each workspace gets its own Qdrant collection - Indexing only needs to run once per project - Search works across all indexed files