File Watcher → Embedding Service → Qdrant Manager
                                        ↑
MCP Client (Claude) ←── MCP Server ────┘
                         (code_search)

pip install -r requirements.txt

cp .env.example .env
# Edit .env with your Qdrant URL, Qdrant API key, OpenAI API key, and watch directory

python run_mcp_server.py

{
  "mcpServers": {
    "code-vector-search": {
      "command": "python",
      "args": ["/path/to/code-vector-sync/run_mcp_server.py"],
      "env": {
        "QDRANT_URL": "your-qdrant-url",
        "QDRANT_API_KEY": "your-api-key",
        "OPENAI_API_KEY": "your-openai-key"
      }
    }
  }
}

code-vector-sync/
├── src/
│   ├── mcp_server.py        # MCP server entry point and tool definitions
│   ├── code_search.py       # Search query handling
│   ├── code_sync_service.py # Orchestrates watching, embedding, and indexing
│   ├── embedding_service.py # OpenAI embedding calls
│   ├── file_watcher.py      # Watchdog-based directory monitoring
│   └── qdrant_manager.py    # Qdrant client and collection management
├── run_mcp_server.py        # Launcher script
├── requirements.txt
├── .env.example             # Template — copy to .env and fill in values
└── .gitignore