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Gemini RAG MCP Server

A Model Context Protocol (MCP) server that provides RAG (Retrieval-Augmented Generation) capabilities using Google's Gemini API File Search feature. This server enables AI applications to create knowledge bases and retrieve information from uploaded documents.

Features

  • File Search RAG: Create and manage knowledge bases using Gemini's File Search API

  • Document Upload: Upload files and text content to create searchable knowledge bases

  • Information Retrieval: Query knowledge bases to retrieve relevant information

  • Configurable Models: Choose Gemini models via environment variable

  • MCP Protocol: Full compatibility with Model Context Protocol

  • Type-Safe: Full TypeScript support with strict mode enabled

  • Dual Transport Support: stdio (default) and HTTP transports

  • Production-Ready: Logging, error handling, and configuration management

Prerequisites

  • Node.js >= 22.10.0

  • pnpm >= 10.19.0

  • Google API Key with Gemini API access

Installation

Using with Claude Desktop (Recommended)

Add the following to your Claude Desktop configuration file:

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

{ "mcpServers": { "gemini-rag-mcp": { "command": "npx", "args": ["-y", "@r_masseater/gemini-rag-mcp"], "env": { "GOOGLE_API_KEY": "your_google_api_key_here", "STORE_DISPLAY_NAME": "your_store_name" } } } }

Required Environment Variables:

  • GOOGLE_API_KEY: Your Google API key with Gemini API access

  • STORE_DISPLAY_NAME: Display name for your vector store/knowledge base

Optional Environment Variables:

  • GEMINI_MODEL: Gemini model to use for queries (default: gemini-2.5-pro)

    • Options: gemini-2.5-pro, gemini-2.5-flash

After configuration, restart Claude Desktop to load the server.

Development

1. Clone the repository

git clone https://github.com/masseater/gemini-rag-mcp.git cd gemini-rag-mcp

2. Install dependencies

pnpm install

3. Run in development mode

# stdio transport (default) pnpm run dev # HTTP transport (with hot reload) pnpm run dev:http

Environment Variables

Required:

  • GOOGLE_API_KEY: Google API key with Gemini API access

  • STORE_DISPLAY_NAME: Display name for vector store/knowledge base

Optional:

  • GEMINI_MODEL: Gemini model for queries (default: gemini-2.5-pro)

  • LOG_LEVEL: Logging level (error|warn|info|debug, default: info)

  • DEBUG: Enable debug console output (true|false, default: false)

  • PORT: HTTP server port (default: 3000)

Available Tools

Once configured with Claude Desktop, the following tools are available:

  • upload_file: Upload document files to the knowledge base

  • upload_content: Upload text content directly to the knowledge base

  • query: Query the knowledge base using RAG

Resources

License

MIT License

-
security - not tested
A
license - permissive license
-
quality - not tested

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