A Model Context Protocol (MCP) server that wraps the Gemini CLI, allowing AI assistants like Claude to use Gemini for research and analysis tasks.
Disclaimer: This is an unofficial, community-developed tool that wraps the Google Gemini CLI. It is not affiliated with, endorsed by, or sponsored by Google. All Google and Gemini trademarks, service marks, and logos are the property of Google LLC. This project is licensed under the MIT License.
Important: This tool requires that you have the Gemini CLI installed and authenticated on your system. See the Prerequisites section for details.
- gemini_prompt: Send prompts to Gemini and get responses
- gemini_research: Research topics with optional file context
- gemini_analyze_code: Analyze code files for reviews, explanations, optimizations, security, or testing
- gemini_summarize: Summarize content from text or files
# Install from GitHub (latest)
uvx --from git+https://github.com/DiversioTeam/gemini-cli-mcp gemini-mcp
# Or from PyPI (when published)
uvx gemini-mcpgit clone https://github.com/DiversioTeam/gemini-cli-mcp
cd gemini-cli-mcp
uv sync
uv run gemini-mcpEnsure you have Python 3.10, 3.11, 3.12, or 3.13 installed. The project is tested on all these versions.
This MCP server requires the Gemini CLI to be installed and authenticated:
- Install Gemini CLI: Follow the official installation instructions for your platform
- Authenticate: Run
gemini auth loginand follow the prompts - Verify: Test that it works by running
gemini -p "Hello, world!"
If you see an authentication error, make sure you've completed the login process.
You'll need an MCP-compatible client such as:
- Claude Desktop
- Other MCP-compatible AI assistants
Before running the server, verify your setup:
# Check if everything is configured correctly
gemini-mcp setupThis will check:
- Gemini CLI installation
- Authentication status
- Environment configuration
If you see authentication errors, run:
gemini auth login# Method 1: Run from current directory (for development)
uv run gemini-mcp
# Method 2: Run using uvx from GitHub
uvx --from git+https://github.com/DiversioTeam/gemini-cli-mcp gemini-mcp
# Method 3: Run if installed globally
gemini-mcp
# With debug logging
LOG_LEVEL=DEBUG gemini-mcp# Install from GitHub (use -- separator for proper argument parsing)
claude mcp add gemini uvx -- --from git+https://github.com/DiversioTeam/gemini-cli-mcp.git gemini-mcp
# Or install from PyPI when published
claude mcp add gemini uvx -- gemini-mcpAdd this to ~/.config/claude-code/mcp-settings.json:
{
"servers": {
"gemini": {
"command": "uvx",
"args": ["--from", "git+https://github.com/DiversioTeam/gemini-cli-mcp.git", "gemini-mcp"]
}
}
}Add this to your Claude Desktop configuration:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
Linux: ~/.config/claude/claude_desktop_config.json
{
"mcpServers": {
"gemini": {
"command": "uvx",
"args": ["--from", "git+https://github.com/DiversioTeam/gemini-cli-mcp.git", "gemini-mcp"],
"env": {
"LOG_LEVEL": "INFO"
}
}
}
}Send a simple prompt to Gemini.
Parameters:
prompt(required): The prompt to sendmodel(optional): The Gemini model to use (default: gemini-2.5-pro)context(optional): Additional context to prepend to the prompt
Research a topic with optional file context.
Parameters:
topic(required): The research topic or questionfiles(optional): List of file paths to include as contextmodel(optional): The Gemini model to use
Analyze code files for various purposes.
Parameters:
files(required): List of code files to analyzeanalysis_type(required): Type of analysis - one of:review: Code review for issues and improvementsexplain: Detailed explanation of the codeoptimize: Performance and maintainability suggestionssecurity: Security vulnerability analysistest: Test case suggestions
specific_question(optional): Additional specific questionmodel(optional): The Gemini model to use
Summarize content from text or files.
Parameters:
content(optional): Text content to summarizefiles(optional): Files to summarize (alternative to content)summary_type(optional): Type of summary - one of:brief: 2-3 sentence summary (default)detailed: Comprehensive summarybullet_points: Bullet point formatexecutive: Executive summary for decision makers
model(optional): The Gemini model to use
Note: Either content or files must be provided.
This MCP server implements several security measures:
- Sandboxed file access: By default, file access is restricted to the current working directory
- Path validation: All file paths are validated to prevent directory traversal attacks
- Configurable allowed directories: You can specify allowed directories via:
- Constructor parameter:
GeminiMCPServer(allowed_directories=["/path/to/safe/dir"]) - Environment variable:
GEMINI_MCP_ALLOWED_DIRS=/path1:/path2:/path3
- Constructor parameter:
- All user inputs are properly sanitized before being passed to the CLI
- Command injection is prevented by using subprocess with argument lists (never shell=True)
- File paths are resolved and validated before use
- Always run the server with minimal required permissions
- Regularly update both the MCP server and Gemini CLI
- Monitor logs for any suspicious activity
-
Clone the repository:
git clone https://github.com/DiversioTeam/gemini-cli-mcp.git cd gemini-cli-mcp -
Install development dependencies:
uv sync --all-extras --dev
-
Install pre-commit hooks:
uv run pre-commit install
You can add the server for local testing with Claude Code CLI:
# Method 1: Add from local directory (for development)
claude mcp add gemini-local -- uv run gemini-mcp
# Method 2: Add from PyPI (when published)
claude mcp add gemini uvx -- gemini-mcp
# Method 3: Add from GitHub (development version)
claude mcp add gemini uvx -- --from git+https://github.com/DiversioTeam/gemini-cli-mcp.git gemini-mcp
# Then you can test the functionality immediately
# Example: Send prompts, research topics, analyze code, etc.# Run all tests with coverage
uv run pytest
# Run specific test file
uv run pytest tests/test_tools.py
# Run with verbose output
uv run pytest -v# Run linting
uv run ruff check .
# Run formatting
uv run ruff format .
# Run type checking
uv run mypy src/
# Run security checks
uv run ruff check --select S .Run the setup check to diagnose common issues:
gemini-mcp setup-
"Gemini CLI not found in PATH"
- Ensure Gemini CLI is installed:
which gemini - Add Gemini to your PATH if needed
- Follow the installation guide for your platform
- Ensure Gemini CLI is installed:
-
Authentication errors
- The server will detect if you're not authenticated
- Run
gemini auth loginto authenticate - Check if your credentials have expired
- The error message will guide you on what to do
-
File access errors
- Check that files are within allowed directories
- Use absolute paths or ensure relative paths are correct
- Set
GEMINI_MCP_ALLOWED_DIRSfor custom directories
-
"Command not found" errors
- Run
gemini-mcp setupto check your installation - Ensure you've installed the package:
uv pip install -e .
- Run
Enable debug logging to see detailed information:
LOG_LEVEL=DEBUG gemini-mcpWe welcome contributions! Please:
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Make your changes and add tests
- Ensure all tests pass and code quality checks succeed
- Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
This project is licensed under the MIT License - see the LICENSE file for details.
- Built on top of the Model Context Protocol
- Integrates with Google's Gemini CLI (unofficial integration)
- Inspired by the MCP ecosystem and community