Gemini Mcp

@RLabs-Inc

About Gemini Mcp

MCP Server that enables Claude code to interact with Gemini

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "gemini-mcp": {
      "command": "bun",
      "args": [
        "run",
        "build"
      ]
    }
  }
}

Tools

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Overview

What is Gemini Mcp?

Gemini Mcp is a Model Context Protocol (MCP) server that integrates Google's Gemini 3 models with Claude Code, enabling direct access to Gemini's capabilities—such as image/video generation, deep research, code execution, and web search—from within a Claude Code session. It is designed for developers who want to combine Gemini's creative and analytical tools with Claude's coding and reasoning workflows, and it also ships with a standalone CLI.

How to use Gemini Mcp?

Install via npm (@rlabs-inc/gemini-mcp) and add it to Claude Code with claude mcp add gemini -s user -- env GEMINI_API_KEY=YOUR_KEY npx -y @rlabs-inc/gemini-mcp. Alternatively, install globally (npm install -g @rlabs-inc/gemini-mcp) and use the gcli CLI. Set your API key once with gcli config set api-key YOUR_KEY and then invoke any tool (e.g., gcli image, gcli search) directly from the terminal.

Key features of Gemini Mcp

Deep research agent with web search and citations
4K image generation with 10 aspect ratios
Multi-turn image editing through conversation
Video generation using Veo 2.0 (async polling)
Code execution with Python libraries (numpy, pandas, matplotlib)
Real-time web search with inline citations

Use cases of Gemini Mcp

Generate UI mockups and React components during a Claude Code development session
Analyze YouTube videos by URL with timestamp clipping and summarization
Extract tables and data from PDFs, DOCX, and spreadsheets
Brainstorm solutions collaboratively between Claude and Gemini
Summarize long documents at configurable detail levels (brief, moderate, detailed)

FAQ from Gemini Mcp

What API key is required?

A Google Gemini API key from Google AI Studio — it is free and takes seconds to obtain.

How do I handle rate limits (429 errors)?

Set GEMINI_MODEL=gemini-3-flash-preview to use the Flash model for initialization (higher rate limits), or upgrade to a paid Google AI plan.

Where are generated files saved?

Files are saved to the directory specified by GEMINI_OUTPUT_DIR (defaults to ./gemini-output in the working directory).

What models does Gemini Mcp use?

It uses Gemini 3 Pro/Flash for queries, Nano Banana Pro for images, Veo 2.0 for videos, and supports configurable model overrides via environment variables.

How can I troubleshoot connection issues?

Verify your API key at Google AI Studio, check the server status with claude mcp list, and enable verbose logging by setting VERBOSE=true in the environment.

Frequently asked questions

What API key is required?

A Google Gemini API key from [Google AI Studio](https://aistudio.google.com/apikey) — it is free and takes seconds to obtain.

How do I handle rate limits (429 errors)?

Set `GEMINI_MODEL=gemini-3-flash-preview` to use the Flash model for initialization (higher rate limits), or upgrade to a paid Google AI plan.

Where are generated files saved?

Files are saved to the directory specified by `GEMINI_OUTPUT_DIR` (defaults to `./gemini-output` in the working directory).

What models does Gemini Mcp use?

It uses Gemini 3 Pro/Flash for queries, Nano Banana Pro for images, Veo 2.0 for videos, and supports configurable model overrides via environment variables.

How can I troubleshoot connection issues?

Verify your API key at Google AI Studio, check the server status with `claude mcp list`, and enable verbose logging by setting `VERBOSE=true` in the environment.

Comments

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