🗄️ LanceDB MCP Server for LLMS


A Model Context Protocol (MCP) server that enables LLMs to interact directly the documents that they have on-disk through agentic RAG and hybrid search in LanceDB. Ask LLMs questions about the dataset as a whole or about specific documents.

✨ Features

- 🔍 LanceDB-powered serverless vector index and document summary catalog.
- 📊 Efficient use of LLM tokens. The LLM itself looks up what it needs when it needs.
- 📈 Security. The index is stored locally so no data is transferred to the Cloud when using a local LLM.

🚀 Quick Start

To get started, create a local directory to store the index and add this configuration to your Claude Desktop config file:

MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
Windows: %APPDATA%/Claude/claude_desktop_config.json

``json
{
"mcpServers": {
"lancedb": {
"command": "npx",
"args": [
"lance-mcp",
"PATH_TO_LOCAL_INDEX_DIR"
]
}
}
}
`

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- Node.js 18+
- npx
- MCP Client (Claude Desktop App for example)
- Summarization and embedding models installed (see config.ts - by default we use Ollama models)
- ollama pull snowflake-arctic-embed2
- ollama pull llama3.1:8b

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#### Local Development Mode:

`json
{
"mcpServers": {
"lancedb": {
"command": "node",
"args": [
"PATH_TO_LANCE_MCP/dist/index.js",
"PATH_TO_LOCAL_INDEX_DIR"
]
}
}
}
`
Use npm run build to build the project.

Use npx @modelcontextprotocol/inspector dist/index.js PATH_TO_LOCAL_INDEX_DIR to run the MCP tool inspector.

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The seed script creates two tables in LanceDB - one for the catalog of document summaries, and another one - for vectorized documents' chunks.
To run the seed script use the following command:
`console
npm run seed -- --dbpath --filesdir
`

You can use sample data from the docs/ directory. Feel free to adjust the default summarization and embedding models in the config.ts file. If you need to recreate the index, simply rerun the seed script with the --overwrite option.

#### Catalog

- Document summary
- Metadata

#### Chunks

- Vectorized document chunk
- Metadata

🎯 Example Prompts

Try these prompts with Claude to explore the functionality:

`plaintext
"What documents do we have in the catalog?"
"Why is the US healthcare system so broken?"
`

📝 Available Tools

The server provides these tools for interaction with the index:

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- catalog_search: Search for relevant documents in the catalog

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- chunks_search: Find relevant chunks based on a specific document from the catalog
- all_chunks_search`: Find relevant chunks from all known documents

📜 License

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