The Gemini MCP Tool serves as a Model Context Protocol server that enables AI assistants to interact with the Google Gemini CLI for advanced analysis and secure code execution.
Key capabilities:
- AI-powered analysis: Ask Gemini questions, analyze large files using
@
syntax (e.g.,@src/main.js
or entire directories@.
), and use the/analyze
command. Supports model selection (-m
) for choosing specific Gemini models likegemini-2.5-flash
. - Sandbox testing: Safely execute and validate code or potentially risky operations in an isolated environment without affecting the local system, using the
sandbox-test
tool or/sandbox
command. - Utility functions: Test server connectivity with the
Ping
command (defaults to 'Pong!') and access Gemini CLI help documentation through theHelp
command.
Allows interaction with the Google Gemini CLI, enabling large-context analysis of files and codebases, answering general knowledge questions, and providing a sandbox environment for safely executing code.
Leverages Node.js as a runtime environment for the MCP server, supporting execution of the Gemini MCP Tool and its capabilities.
Can be installed and used within Gemini's sandbox environment for data visualization and analysis tasks.
Supports creation and execution of Python scripts within Gemini's sandbox environment for data processing and testing.
Mentioned as a topic for which users can request best practices information through the Gemini integration.
Update branch is now live! 2.0.0 is a complete refactor from 1.1.1 (npm version). This change will hopefully speed up future development. See and test 2.0.0 --> update branch --> "Gemini Reads, Claude edits, Save Claude Tokens" .
🚀 Share your experience! Tell us how it went and help the community grow!
📚 Wiki documentation is available with additional guides and examples.
The contribution framework is currently in testing. Our goal is to use Gemini to create gemini-mcp-tool extensions, automate tool creation, and provide a TUI-based tool generator.
Gemini MCP Tool
📚 View Full Documentation - Search me!, Examples, FAQ, Troubleshooting, Best Practices
This is a simple Model Context Protocol (MCP) server that allows AI assistants to interact with the Gemini CLI. It enables the AI to leverage the power of Gemini's massive token window for large analysis, especially with large files and codebases using the @
syntax for direction.
TLDR: +
Goal: Use Gemini's powerful analysis capabilities directly in Claude Code to save tokens and analyze large files.
One-Line Setup
Verify Installation
Type /mcp
inside Claude Code to verify the gemini-cli MCP is active.
Alternative: Import from Claude Desktop
If you already have it configured in Claude Desktop:
- Add to your Claude Desktop config:
- Import to Claude Code:
Prerequisites
Before using this tool, ensure you have:
- Node.js (v16.0.0 or higher)
- Google Gemini CLI installed and configured
Installation Options
Option 1: NPX (Recommended)
No installation required - the tool runs directly via npx
.
Option 2: Global Installation
Configuration
Register the MCP server with your MCP client:
For NPX Usage (Recommended)
Add this configuration to your Claude Desktop config file:
For Global Installation
If you installed globally, use this configuration instead:
Configuration File Locations:
- Claude Desktop:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json
- Windows:
%APPDATA%\Claude\claude_desktop_config.json
- Linux:
~/.config/claude/claude_desktop_config.json
- macOS:
After updating the configuration, restart your terminal session.
Available Commands
- Natural language: "use gemini to explain index.html", "understand the massive project using gemini", "ask gemini to search for latest news"
- Claude Code: Type
/gemini-cli
and commands will populate in Claude Code's interface.
Usage Examples
With File References (using @ syntax)
ask gemini to analyze @src/main.js and explain what it does
use gemini to summarize @. the current directory
analyze @package.json and tell me about dependencies
General Questions (without files)
ask gemini to search for the latest tech news
use gemini to explain quantum computing
ask gemini about best practices for React development related to @file_im_confused_about
Using Gemini CLI's Sandbox Mode (-s)
The sandbox mode allows you to safely test code changes, run scripts, or execute potentially risky operations in an isolated environment.
use gemini sandbox to create and run a Python script that processes data
ask gemini to safely test @script.py and explain what it does
use gemini sandbox to install numpy and create a data visualization
test this code safely: Create a script that makes HTTP requests to an API
Tools (for the AI)
These tools are designed to be used by the AI assistant.
ask-gemini
: Asks Google Gemini for its perspective. Can be used for general questions or complex analysis of files.prompt
(required): The analysis request. Use the@
syntax to include file or directory references (e.g.,@src/main.js explain this code
) or ask general questions (e.g.,Please use a web search to find the latest news stories
).model
(optional): The Gemini model to use. Defaults togemini-2.5-flash
.sandbox
(optional): Set totrue
to run in sandbox mode for safe code execution.
sandbox-test
: Safely executes code or commands in Gemini's sandbox environment. Always runs in sandbox mode.prompt
(required): Code testing request (e.g.,Create and run a Python script that...
or@script.py Run this safely
).model
(optional): The Gemini model to use.
Ping
: A simple test tool that echoes back a message.Help
: Shows the Gemini CLI help text.
Slash Commands (for the User)
You can use these commands directly in Claude Code's interface (compatibility with other clients has not been tested).
- /analyze: Analyzes files or directories using Gemini, or asks general questions.
prompt
(required): The analysis prompt. Use@
syntax to include files (e.g.,/analyze prompt:@src/ summarize this directory
) or ask general questions (e.g.,/analyze prompt:Please use a web search to find the latest news stories
).
- /sandbox: Safely tests code or scripts in Gemini's sandbox environment.
prompt
(required): Code testing request (e.g.,/sandbox prompt:Create and run a Python script that processes CSV data
or/sandbox prompt:@script.py Test this script safely
).
- /help: Displays the Gemini CLI help information.
- /ping: Tests the connection to the server.
message
(optional): A message to echo back.
Contributing
Contributions are welcome! Please see our Contributing Guidelines for details on how to submit pull requests, report issues, and contribute to the project.
License
This project is licensed under the MIT License. See the LICENSE file for details.
Disclaimer: This is an unofficial, third-party tool and is not affiliated with, endorsed, or sponsored by Google.
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.
A Model Context Protocol server that enables AI assistants to interact with Google Gemini CLI, allowing them to leverage Gemini's large token window for analyzing files and codebases using natural language commands.
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