-
securityF
license-
qualityA server implementing the Model Context Protocol that enables AI assistants like Claude to interact with Google's Gemini API for text generation, text analysis, and chat conversations.
Last updated -
Integrates with Google's Gemini AI models (including variants like gemini-2.5-pro-preview, gemini-1.5-pro, etc.) to provide AI capabilities with automatic fallback mechanisms between experimental and stable models.
Gemini MCP Server
A Model Context Protocol (MCP) server that enables Claude to collaborate with Google's Gemini AI models.
Features
š¤ Multiple Gemini Tools: Ask questions, review code, brainstorm ideas, generate tests, and get explanations
š Dual-Model Support: Automatic fallback from experimental to stable models
ā” Configurable Models: Easy switching between different Gemini variants
š”ļø Reliable: Never lose functionality with automatic model fallback
š Transparent: Shows which model was used for each response
Quick Start
1. Prerequisites
Python 3.9+
2. Installation
# Clone the repository
git clone https://github.com/lbds137/gemini-mcp-server.git
cd gemini-mcp-server
# Install dependencies
pip install -r requirements.txt
# Copy and configure environment
cp .env.example .env
# Edit .env and add your GEMINI_API_KEY
3. Configuration
Edit .env to configure your models:
# Your Gemini API key (required)
GEMINI_API_KEY=your_api_key_here
# Model configuration (optional - defaults shown)
GEMINI_MODEL_PRIMARY=gemini-2.5-pro-preview-06-05
GEMINI_MODEL_FALLBACK=gemini-1.5-pro
GEMINI_MODEL_TIMEOUT=10000
4. Development Setup
For development with PyCharm or other IDEs:
# Create virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install in development mode
pip install -e .
# Run tests
python -m pytest
5. Register with Claude
# Install to MCP location
./scripts/install.sh
# Or manually register
claude mcp add gemini-collab python3 ~/.claude-mcp-servers/gemini-collab/server.py
Available Tools
ask_gemini
General questions and problem-solving assistance.
gemini_code_review
Get code review feedback focusing on security, performance, and best practices.
gemini_brainstorm
Collaborative brainstorming for architecture and design decisions.
gemini_test_cases
Generate comprehensive test scenarios for your code.
gemini_explain
Get clear explanations of complex code or concepts.
server_info
Check server status and model configuration.
Model Configurations
Best Quality (Default)
GEMINI_MODEL_PRIMARY=gemini-2.5-pro-preview-06-05
GEMINI_MODEL_FALLBACK=gemini-1.5-pro
Best Performance
GEMINI_MODEL_PRIMARY=gemini-2.5-flash-preview-05-20
GEMINI_MODEL_FALLBACK=gemini-2.0-flash
Most Cost-Effective
GEMINI_MODEL_PRIMARY=gemini-2.0-flash
GEMINI_MODEL_FALLBACK=gemini-2.0-flash-lite
Development
Project Structure
gemini-mcp-server/
āāā src/
ā āāā gemini_mcp/
ā āāā __init__.py
ā āāā server.py # Main server with DualModelManager
āāā tests/
ā āāā test_server.py
āāā scripts/
ā āāā install.sh # Quick installation script
ā āāā install.sh # Install/update deployment script
ā āāā dev-link.sh # Development symlink script
āāā docs/
ā āāā BUILD_YOUR_OWN_MCP_SERVER.md
āāā .claude/
ā āāā settings.json # Claude Code permissions
āāā .env # Your configuration (git-ignored)
āāā .env.example # Example configuration
āāā .gitignore
āāā CLAUDE.md # Instructions for Claude Code
āāā LICENSE
āāā README.md # This file
āāā docs/
ā āāā BUILD_YOUR_OWN_MCP_SERVER.md
ā āāā DUAL_MODEL_CONFIGURATION.md # Dual-model setup guide
ā āāā PYCHARM_SETUP.md
ā āāā TESTING.md
āāā requirements.txt
āāā setup.py
āāā package.json # MCP registration metadata
āāā package-lock.json
Running Tests
python -m pytest tests/ -v
Contributing
Fork the repository
Create a feature branch (
git checkout -b feature/amazing-feature)Commit your changes (
git commit -m 'Add amazing feature')Push to the branch (
git push origin feature/amazing-feature)Open a Pull Request
Updating
To update your local MCP installation after making changes:
./scripts/install.sh
This script intelligently handles both installation and updates.
Troubleshooting
Server not found
# Check registration
claude mcp list
# Re-register if needed
./scripts/install.sh
API Key Issues
# Verify environment variable
echo $GEMINI_API_KEY
# Test directly
python -c "import google.generativeai as genai; genai.configure(api_key='$GEMINI_API_KEY'); print('ā
API key works')"
Model Availability
Some models may not be available in all regions. Check the fallback model in logs if primary fails consistently.
License
MIT License - see LICENSE file for details.
Acknowledgments
Built for Claude using the Model Context Protocol
Powered by Google's Gemini AI
This server cannot be installed
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