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LanceDB MCP Server

by RyanLisse
GitHub
Python
3
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LanceDB MCP Server

Overview

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.

Components

Resources

The server exposes vector database tables as resources:

  • table://{name}: A vector database table that stores embeddings and metadata
    • Configurable vector dimensions
    • Text metadata support
    • Efficient similarity search capabilities

API Endpoints

Table Management
  • POST /table
    • Create a new vector table
    • Input:
      { "name": "my_table", # Table name "dimension": 768 # Vector dimension }
Vector Operations
  • POST /table/{table_name}/vector
    • Add vector data to a table
    • Input:
      { "vector": [0.1, 0.2, ...], # Vector data "text": "associated text" # Metadata }
  • POST /table/{table_name}/search
    • Search for similar vectors
    • Input:
      { "vector": [0.1, 0.2, ...], # Query vector "limit": 10 # Number of results }

Installation

# Clone the repository git clone https://github.com/yourusername/lancedb_mcp.git cd lancedb_mcp # Install dependencies using uv uv pip install -e .

Usage with Claude Desktop

# Add the server to your claude_desktop_config.json "mcpServers": { "lancedb": { "command": "uv", "args": [ "run", "python", "-m", "lancedb_mcp", "--db-path", "~/.lancedb" ] } }

Development

# Install development dependencies uv pip install -e ".[dev]" # Run tests pytest # Format code black . ruff .

Environment Variables

  • LANCEDB_URI: Path to LanceDB storage (default: ".lancedb")

License

This project is licensed under the MIT License. See the LICENSE file for details.

This server cannot be installed

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license - not found
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quality - not tested

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Enables efficient vector database operations for embedding storage and similarity search through a Model Context Protocol interface.

  1. Overview
    1. Components
      1. Resources
      2. API Endpoints
    2. Installation
      1. Usage with Claude Desktop
        1. Development
          1. Environment Variables
            1. License

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