LanceDB
A vector database server for storing, searching, and managing vector embeddings.
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.
Related Servers
Memory-Plus
a lightweight, local RAG memory store to record, retrieve, update, delete, and visualize persistent "memories" across sessions—perfect for developers working with multiple AI coders (like Windsurf, Cursor, or Copilot) or anyone who wants their AI to actually remember them.
PostgreSQL MCP Server
An MCP server that provides tools to interact with PostgreSQL databases.
Sefaria Jewish Library MCP Server
Provides access to Jewish texts from the Sefaria library.
Qdrant
Implement semantic memory layer on top of the Qdrant vector search engine
Trino MCP Server
A Go implementation of a Model Context Protocol (MCP) server for Trino, enabling LLM models to query distributed SQL databases through standardized tools.
Videoschiri
Fussball. Live. Alle Spiele, alle TV-Sender und Streams.
JDBC-MCP
Enables AI assistants to interact with various databases through JDBC connections.
FHIR MCP Server by CData
A read-only MCP server for FHIR, enabling LLMs to query live FHIR data. Requires the CData JDBC Driver for FHIR.
Unofficial Reactome MCP Server
Access Reactome pathway and systems biology data via its live API.
ChromaDB MCP
An MCP server for vector storage and retrieval using ChromaDB.