LanceDB Vector Database
STDIOMCP server implementation for vector database operations and similarity search.
MCP server implementation for vector database operations and similarity search.
A Model Context Protocol (MCP) server implementation for LanceDB vector database operations. This server enables efficient vector storage, similarity search, and management of vector embeddings with associated metadata.
The server exposes vector database tables as resources:
table://{name}
: A vector database table that stores embeddings and metadata
POST /table
{ "name": "my_table", # Table name "dimension": 768 # Vector dimension }
POST /table/{table_name}/vector
{ "vector": [0.1, 0.2, ...], # Vector data "text": "associated text" # Metadata }
POST /table/{table_name}/search
{ "vector": [0.1, 0.2, ...], # Query vector "limit": 10 # Number of results }
# Clone the repository git clone https://github.com/yourusername/lancedb_mcp.git cd lancedb_mcp # Install dependencies using uv uv pip install -e .
# Add the server to your claude_desktop_config.json "mcpServers": { "lancedb": { "command": "uv", "args": [ "run", "python", "-m", "lancedb_mcp", "--db-path", "~/.lancedb" ] } }
# Install development dependencies uv pip install -e ".[dev]" # Run tests pytest # Format code black . ruff .
LANCEDB_URI
: Path to LanceDB storage (default: ".lancedb")This project is licensed under the MIT License. See the LICENSE file for details.