Provides RAG (Retrieval-Augmented Generation) capabilities using Google's Gemini API File Search feature, enabling creation of knowledge bases from uploaded documents and text content for information retrieval.
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
Required Environment Variables:
GOOGLE_API_KEY: Your Google API key with Gemini API accessSTORE_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
2. Install dependencies
3. Run in development mode
Environment Variables
Required:
GOOGLE_API_KEY: Google API key with Gemini API accessSTORE_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
This server cannot be installed
remote-capable server
The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.
Enables creation and querying of knowledge bases using Google's Gemini API File Search feature, allowing AI applications to upload documents and retrieve information through RAG (Retrieval-Augmented Generation).