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Gemini Image Generation MCP

@collactivelabs

Repository

About Gemini Image Generation MCP

A Model Calling Protocol (MCP) server that allows Claude and other LLMs to generate images using Google's Gemini AI model.

#gemini#image-generation#mcp

Config

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

{
  "mcpServers": {
    "openai-image-generation": {
      "command": "node",
      "args": [
        "/full/path/to/openai-image-gen-mcp/src/mcp-server.js"
      ],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key-here"
      }
    }
  }
}

Tools

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Overview

What is Gemini Image Generation MCP?

Gemini Image Generation MCP is an MCP server that enables LLMs like Claude to generate images using Google's Gemini AI model (gemini-2.0-flash-preview-image-generation). It saves generated images locally and includes an interactive web interface for testing and demonstration.

How to use Gemini Image Generation MCP?

Install Node.js 18+, clone the repository, install dependencies (npm install), and set your GEMINI_API_KEY in the .env file. Run the MCP server with node src/mcp-server.js or use Docker. Configure Claude or another MCP client to connect via the MCP protocol—either through JSON configuration or the Claude console’s MCPs section.

Key features of Gemini Image Generation MCP

  • Generate images from text prompts using Google’s Gemini model.
  • Save generated images locally.
  • Configure generation parameters like temperature, topK, and topP.
  • Interactive web interface for testing and demonstration.
  • Docker support for easy deployment.
  • Simple MCP standard implementation.

Use cases of Gemini Image Generation MCP

  • Enable Claude to generate images as part of conversations.
  • Automate image creation for content generation pipelines.
  • Test and demo Gemini image generation capabilities via the web interface.
  • Integrate image generation into custom applications using the MCP protocol.

FAQ from Gemini Image Generation MCP

What do I need to run this server?

You need Node.js 18 or higher and a Google API key with access to the Gemini API (specifically the image generation preview model). Docker is optional but supported.

How do I configure the server?

Create a .env file from .env.example and set GEMINI_API_KEY (required). Optional settings include MCP_AUTH_TOKEN, PORT, OUTPUT_DIR, and LOG_LEVEL.

How does the server integrate with Claude?

You can add the MCP server configuration in Claude’s settings via JSON or through the Claude console’s MCPs section, specifying the server URL and any authentication token.

Where are generated images saved?

By default, images are saved in the ./generated-images directory, configurable via the OUTPUT_DIR environment variable.

What Gemini model is used for generation?

The server uses the gemini-2.0-flash-preview-image-generation model, which is optimized for image generation tasks.

Frequently asked questions

What do I need to run this server?

You need Node.js 18 or higher and a Google API key with access to the Gemini API (specifically the image generation preview model). Docker is optional but supported.

How do I configure the server?

Create a `.env` file from `.env.example` and set `GEMINI_API_KEY` (required). Optional settings include `MCP_AUTH_TOKEN`, `PORT`, `OUTPUT_DIR`, and `LOG_LEVEL`.

How does the server integrate with Claude?

You can add the MCP server configuration in Claude’s settings via JSON or through the Claude console’s MCPs section, specifying the server URL and any authentication token.

Where are generated images saved?

By default, images are saved in the `./generated-images` directory, configurable via the `OUTPUT_DIR` environment variable.

What Gemini model is used for generation?

The server uses the `gemini-2.0-flash-preview-image-generation` model, which is optimized for image generation tasks.

Comments

Basic information

Category

AI & Agents

Transports

stdio

Author

collactivelabs

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