houseworthe/gemini-mcp-server

Gemini MCP Server for Claude Code

A Model Context Protocol (MCP) server that seamlessly integrates Google's Gemini AI capabilities into Claude Code, enabling powerful AI collaboration.

Features

This MCP server provides Claude with access to Gemini's capabilities through four powerful tools:

• Ask Gemini - Direct question-answering using Gemini's extensive knowledge base
• Code Review - Comprehensive code analysis with support for large codebases
• Brainstorming - Creative ideation and problem-solving assistance
• Large Content Analysis - Analyze extensive documents, logs, or codebases (optimized for 1M+ tokens)

Use Cases

Enhanced Code Development

# Claude can leverage Gemini for specialized tasks:
"Claude, ask Gemini to review this React component for performance optimizations"
"Use Gemini to analyze this entire codebase and identify potential security vulnerabilities"

Collaborative Problem Solving

# Combine Claude's reasoning with Gemini's knowledge:
"Ask Gemini about the latest best practices for microservices architecture"
"Have Gemini brainstorm solutions for scaling our database"

Large-Scale Analysis

# Process extensive content that benefits from Gemini's capabilities:
"Use Gemini to analyze these server logs and identify anomaly patterns"
"Ask Gemini to review this 10,000-line legacy codebase and suggest modernization strategies"

Quick Start

One-Line Installation

curl -sSL https://raw.githubusercontent.com/houseworthe/gemini-mcp-server/main/gemini-mcp/install.sh | bash

Manual Installation

1. Clone this repository:

   git clone https://github.com/houseworthe/gemini-mcp-server.git
   cd gemini-mcp-server
   

2. Get your Gemini API key from Google AI Studio

3. Run the installer:

   cd gemini-mcp
   ./install.sh
   

4. Enter your API key when prompted

Architecture

The server acts as a bridge between Claude Code and Google's Gemini API:

Claude Code <-> MCP Protocol <-> Gemini MCP Server <-> Gemini API

Key Components:

• Async JSON-RPC Handler: Processes MCP protocol messages
• Tool Registry: Manages available Gemini tools
• HTTP Client: Direct API communication with Gemini
• Error Handling: Graceful degradation and timeout management

Configuration

Environment Variables

Create a .env file (see .env.example):

GEMINI_API_KEY=your-api-key-here

Supported Models

• gemini-1.5-flash (default) - Fast responses for most queries
• gemini-1.5-pro - Automatically used for large content analysis

Development

Prerequisites

• Python 3.7+
• Claude CLI
• Gemini API key

Running Tests

python test_server.py

Project Structure

gemini-mcp-server/
├── server.py           # Main MCP server implementation
├── test_server.py      # Integration tests
├── gemini-mcp/         # Distribution package
│   ├── server.py       # Server for end-user installation
│   ├── install.sh      # Installation script
│   ├── setup.sh        # Claude MCP registration
│   └── requirements.txt
└── README.md

API Documentation

Available Tools

ask_gemini

Basic question-answering interface.

{
  "question": "string"  // Required: Your question for Gemini
}

gemini_code_review

Comprehensive code review with contextual understanding.

{
  "code": "string",        // Required: Code to review
  "context": "string",     // Optional: Additional context
  "focus_areas": "string"  // Optional: Specific areas to focus on
}

gemini_brainstorm

Creative ideation and problem-solving.

{
  "topic": "string",       // Required: Topic to brainstorm
  "constraints": "string"  // Optional: Any constraints or requirements
}

gemini_analyze_large

Analyze extensive content with intelligent summarization.

{
  "content": "string",        // Required: Large content to analyze
  "analysis_type": "string",  // Optional: Type of analysis (default: "general")
  "questions": "string"       // Optional: Specific questions to answer
}

Troubleshooting

Server Not Listed

If the server doesn't appear in claude mcp list:

claude mcp remove gemini-collab
claude mcp add --scope user gemini-collab python3 ~/.claude-mcp-servers/gemini-collab/server.py

API Key Issues

• Ensure your API key is valid and has the necessary permissions
• Check that the .env file is in the correct location
• Verify the key is set: echo $GEMINI_API_KEY

Timeout Errors

The server has a 30-second timeout for API calls. For large content:

• Consider breaking it into smaller chunks
• Use the gemini_analyze_large tool which handles content intelligently

Contributing

We welcome contributions! Please see our for details.

Development Setup

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Security

• API keys are stored locally and never transmitted except to Google's API
• All communication uses HTTPS
• The server runs with minimal permissions
• Regular security audits are performed

License

MIT License - see file for details.

Acknowledgments

• Built on the Model Context Protocol by Anthropic
• Powered by Google's Gemini AI
• Inspired by the AI development community

Support

• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Documentation: Wiki

Made with ❤️ by the open source community