Gemini CLI MCP Server

A secure Model Context Protocol (MCP) server that provides access to Google's Gemini CLI functionality through standardized MCP tools.

✨ Features

• 💬 Chat Integration: Direct conversation with Gemini models for development consultation and code assistance
• 🔄 Automatic Fallback: Seamlessly switches from Gemini 2.5 Pro to Flash when quota limits are reached
• 🛡️ Secure Implementation: Uses temporary files to prevent shell injection vulnerabilities
• ⚡ Extended Timeout: 180-second timeout for processing complex queries
• 🚀 Easy Integration: Simple setup with Claude Desktop and other MCP-compatible clients
• 📊 Model Transparency: Response includes information about which model was used (Pro or Flash)

🔧 Prerequisites

1. Node.js 18+ is required
2. Gemini CLI must be installed and authenticated:

   npm install -g @google/generative-ai-cli
   gemini auth

Installation

Install globally via npm:

npm install -g @yusukedev/gemini-cli-mcp

Or use directly with npx:

npx @yusukedev/gemini-cli-mcp

Configuration

Add to your Claude Desktop claude_desktop_config.json file (or similar MCP client configuration):

{
  "mcpServers": {
    "gemini-cli": {
      "command": "npx",
      "args": ["@yusukedev/gemini-cli-mcp"]
    }
  }
}

Or if installed globally:

{
  "mcpServers": {
    "gemini-cli": {
      "command": "gemini-cli-mcp"
    }
  }
}

🛠️ Available Tools

gemini_chat_pro

Chat with Gemini 2.5 Pro for development consultation and code assistance.
If this tool fails（quota exceeded, etc.）, use gemini_chat_flash as a fallback.

Parameters:

• message (required): The message or question to send to Gemini
• context (optional): Additional context or code to include in the conversation

Example:

{
  "name": "gemini_chat_pro",
  "arguments": {
    "message": "Review this TypeScript code for potential improvements",
    "context": "function validateEmail(email: string): boolean { return /\\S+@\\S+\\.\\S+/.test(email); }"
  }
}

gemini_chat_flash

Chat with Gemini 2.5 Flash for development consultation and code assistance.
Use this if gemini_chat_pro fails.

Parameters:

• message (required): The message or question to send to Gemini
• context (optional): Additional context or code to include in the conversation

Example:

{
  "name": "gemini_chat_flash",
  "arguments": {
    "message": "Review this TypeScript code for potential improvements",
    "context": "function validateEmail(email: string): boolean { return /\\S+@\\S+\\.\\S+/.test(email); }"
  }
}

🔄 Automatic Fallback

The server automatically handles quota limits by:

1. Primary: Attempts to use gemini-2.5-pro (high quality)
2. Fallback: Switches to gemini-2.5-flash if Pro quota is exceeded
3. Transparency: Response includes model information and fallback status

📋 System Requirements

• Node.js: 18.0.0 or higher
• OS: Windows, macOS, Linux (with WSL)
• Gemini CLI: Google AI Studio

🐛 Debugging

Since MCP servers operate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:

npm run inspector

📄 License

MIT License

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

🔗 Links

• Model Context Protocol
• Google AI Studio
• Gemini CLI Documentation