MCP cover image
See in Github
2025-01-16

1

Github Watches

7

Github Forks

46

Github Stars

🗄️ LanceDB MCP Server for LLMS

Node.js 18+ License: MIT

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

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

Prerequisites

  • 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

Demo

<img" alt="Lance-MCP image">

Local Development Mode:

{
  "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.

Seed Data

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:

npm run seed -- --dbpath <PATH_TO_LOCAL_INDEX_DIR> --filesdir <PATH_TO_DOCS>

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:

"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:

Catalog Tools

  • catalog_search: Search for relevant documents in the catalog

Chunks Tools

  • 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.

相关推荐

  • https://suefel.com
  • Latest advice and best practices for custom GPT development.

  • Yusuf Emre Yeşilyurt
  • I find academic articles and books for research and literature reviews.

  • https://maiplestudio.com
  • Find Exhibitors, Speakers and more

  • Carlos Ferrin
  • Encuentra películas y series en plataformas de streaming.

  • Joshua Armstrong
  • Confidential guide on numerology and astrology, based of GG33 Public information

  • Contraband Interactive
  • Emulating Dr. Jordan B. Peterson's style in providing life advice and insights.

  • rustassistant.com
  • Your go-to expert in the Rust ecosystem, specializing in precise code interpretation, up-to-date crate version checking, and in-depth source code analysis. I offer accurate, context-aware insights for all your Rust programming questions.

  • Elijah Ng Shi Yi
  • Advanced software engineer GPT that excels through nailing the basics.

  • Emmet Halm
  • Converts Figma frames into front-end code for various mobile frameworks.

  • Alexandru Strujac
  • Efficient thumbnail creator for YouTube videos

  • lumpenspace
  • Take an adjectivised noun, and create images making it progressively more adjective!

  • apappascs
  • 发现市场上最全面,最新的MCP服务器集合。该存储库充当集中式枢纽,提供了广泛的开源和专有MCP服务器目录,并提供功能,文档链接和贡献者。

  • Mintplex-Labs
  • 带有内置抹布,AI代理,无代理构建器,MCP兼容性等的多合一桌面和Docker AI应用程序。

  • ShrimpingIt
  • MCP系列GPIO Expander的基于Micropython I2C的操作,源自ADAFRUIT_MCP230XX

  • n8n-io
  • 具有本机AI功能的公平代码工作流程自动化平台。将视觉构建与自定义代码,自宿主或云相结合,400+集成。

  • open-webui
  • 用户友好的AI接口(支持Ollama,OpenAi API,...)

  • WangRongsheng
  • 🧑‍🚀 llm 资料总结(数据处理、模型训练、模型部署、 o1 模型、mcp 、小语言模型、视觉语言模型)|摘要世界上最好的LLM资源。

  • metorial
  • 数百个MCP服务器的容器化版本📡📡

  • langgenius
  • ravitemer
  • 一个功能强大的Neovim插件,用于管理MCP(模型上下文协议)服务器

    Reviews

    2 (1)
    Avatar
    user_JPEUvMG1
    2025-04-17

    Lance-mcp by adiom-data is a fantastic tool for managing and processing data streams with ease. The flexibility and high performance of this application make it a must-have for any serious developer or data scientist. With its seamless integration and user-friendly interface, I highly recommend checking it out. For more details, visit https://github.com/adiom-data/lance-mcp.