by jamubc
Integrate with Gemini CLI for large-scale file analysis, secure code execution, and advanced context control using Googl
Integrates with Google's Gemini CLI to leverage massive token windows for analyzing large files and codebases, providing general queries, sandbox-mode code execution for safe testing, and structured response handling with behavioral flags for context control.
Gemini CLI is a community-built MCP server published by jamubc that provides AI assistants with tools and capabilities via the Model Context Protocol. Integrate with Gemini CLI for large-scale file analysis, secure code execution, and advanced context control using Googl It is categorized under analytics data, developer tools. This server exposes 6 tools that AI clients can invoke during conversations and coding sessions.
You can install Gemini CLI in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
NOASSERTION
Gemini CLI is released under the NOASSERTION license.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
According to our notes, Gemini CLI benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
We wired Gemini CLI into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Gemini CLI is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
According to our notes, Gemini CLI benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Gemini CLI has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Useful MCP listing: Gemini CLI is the kind of server we cite when onboarding engineers to host + tool permissions.
Gemini CLI is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
According to our notes, Gemini CLI benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Gemini CLI reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Gemini CLI has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
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📚 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.
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Goal: Use Gemini's powerful analysis capabilities directly in Claude Code to save tokens and analyze large files.
Before using this tool, ensure you have:
claude mcp add gemini-cli -- npx -y gemini-mcp-tool
Type /mcp inside Claude Code to verify the gemini-cli MCP is active.
If you already have it configured in Claude Desktop:
"gemini-cli": {
"command": "npx",
"args": ["-y", "gemini-mcp-tool"]
}
claude mcp add-from-claude-desktop
Register the MCP server with your MCP client:
Add this configuration to your Claude Desktop config file:
{
"mcpServers": {
"gemini-cli": {
"command": "npx",
"args": ["-y", "gemini-mcp-tool"]
}
}
}
If you installed globally, use this configuration instead:
{
"mcpServers": {
"gemini-cli": {
"command": "gemini-mcp"
}
}
}
Configuration File Locations:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.json~/.config/claude/claude_desktop_config.jsonAfter updating the configuration, restart your terminal session.
/gemini-cli and commands will populate in Claude Code's interface.ask gemini to analyze @src/main.js and explain what it doesuse gemini to summarize @. the current directoryanalyze @package.json and tell me about dependenciesask gemini to search for the latest tech newsuse gemini to explain div centeringask gemini about best practices for React development related to @file_im_confused_aboutThe 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 dataask gemini to safely test @script.py and explain what it doesuse gemini sandbox to install numpy and create a data visualizationtest this code safely: Create a script that makes HTTP requests to an APIThese 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 to gemini-2.5-pro.sandbox (optional): Set to true 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.You can use these commands directly in Claude Code's interface (compatibility with other clients has not been tested).
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).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).message (optional): A message to echo back.Contributions are welcome! Please see our Contributing Guidelines for details on how to submit pull requests, report issues, and contribute to the project.
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.
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.