How do I install Gemini?

Gemini is a local plugin. Install it using npm package: @chrischall/gemini-mcp and add the generated configuration snippet to your AI app's MCP config file. Then restart your AI app.

What credentials does Gemini need?

Gemini requires the following credentials or environment variables: GEMINI_API_KEY, GEMINI_IMAGE_MODEL, GEMINI_OUTPUT_DIR. You can find setup instructions on the server detail page.

What AI apps work with Gemini?

Gemini uses the Model Context Protocol (MCP) and works with any MCP-compatible AI app, including Claude, ChatGPT / Codex, Gemini, Copilot, Cursor, and more.

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Gemini MCP Server

by Chris Hall

AI & MLLow Risk10.0LocalNew

Free

Generate and edit images with Google Gemini (Nano Banana / Nano Banana Pro) image models.

About

Generate and edit images with Google Gemini (Nano Banana / Nano Banana Pro) image models.

Security Report

10.0

Low Risk10.0Low Risk

Valid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry. Trust signals: trusted author (39/40 approved).

12 files analyzed · 1 issue found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

file_system

Check that this permission is expected for this type of plugin.

env_vars

Check that this permission is expected for this type of plugin.

Shell Command Execution

Runs commands on your machine. Be cautious — only use if you trust this plugin.

What You'll Need

Set these up before or after installing:

Your Google Gemini API key (aistudio.google.com/apikey)Required

Environment variable: GEMINI_API_KEY

Override the default image model (default: gemini-3-pro-image)Optional

Environment variable: GEMINI_IMAGE_MODEL

Default directory for generated images (default: current working directory)Optional

Environment variable: GEMINI_OUTPUT_DIR

How to Install

Add this to your MCP configuration file:

{
  "mcpServers": {
    "io-github-chrischall-gemini-mcp": {
      "env": {
        "GEMINI_API_KEY": "your-gemini-api-key-here",
        "GEMINI_OUTPUT_DIR": "your-gemini-output-dir-here",
        "GEMINI_IMAGE_MODEL": "your-gemini-image-model-here"
      },
      "args": [
        "-y",
        "@chrischall/gemini-mcp"
      ],
      "command": "npx"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

gemini-mcp

MCP server for Google Gemini image generation and editing. Exposes four tools to Claude over stdio: list available models, generate images from text prompts, edit or compose images with text instructions, and generate a consistent set of images from a master prompt. Images are written to disk by default (path returned) or returned inline as base64. Built on the Gemini v1beta API (generativelanguage.googleapis.com) using the Nano Banana / Nano Banana Pro model family.

Developed and maintained by AI (Claude Code).

Environment Variables

Variable	Required	Description
`GEMINI_API_KEY`	Yes	Your Google Gemini API key (aistudio.google.com/apikey)
`GEMINI_IMAGE_MODEL`	No	Override the default image model (default: `gemini-3-pro-image`)
`GEMINI_OUTPUT_DIR`	No	Default directory for generated images (default: current working directory)

Tools

Tool	Description
`gemini_list_models`	List available Gemini image models and the current default
`gemini_generate_image`	Generate image(s) from a text prompt
`gemini_edit_image`	Edit or compose one or more input images with a text instruction
`gemini_generate_set`	Generate a master image plus N consistent images referencing it

Quick Start

{
  "mcpServers": {
    "gemini": {
      "command": "npx",
      "args": ["-y", "@chrischall/gemini-mcp"],
      "env": {
        "GEMINI_API_KEY": "your-api-key-here"
      }
    }
  }
}

See SKILL.md for full usage documentation.