Gemini Image Generator MCP Server

Generate high-quality images from text prompts using Google's Gemini model through the MCP protocol.

Overview

This MCP server allows any AI assistant to generate images using Google's Gemini AI model. The server handles prompt engineering, text-to-image conversion, filename generation, and local image storage, making it easy to create and manage AI-generated images through any MCP client.

Features

• Text-to-image generation using Gemini 2.0 Flash
• Image-to-image transformation based on text prompts
• Support for both file-based and base64-encoded images
• Automatic intelligent filename generation based on prompts
• Automatic translation of non-English prompts
• Local image storage with configurable output path
• Strict text exclusion from generated images
• High-resolution image output
• Direct access to both image data and file path

Available MCP Tools

The server provides the following MCP tools for AI assistants:

1. generate_image_from_text

Creates a new image from a text prompt description.

generate_image_from_text(prompt: str) -> Tuple[bytes, str]

Parameters:

• prompt: Text description of the image you want to generate

Returns:

• A tuple containing:
  • Raw image data (bytes)
  • Path to the saved image file (str)

This dual return format allows AI assistants to either work with the image data directly or reference the saved file path.

Examples:

• "Generate an image of a sunset over mountains"
• "Create a photorealistic flying pig in a sci-fi city"

Example Output

This image was generated using the prompt:

"Hi, can you create a 3d rendered image of a pig with wings and a top hat flying over a happy futuristic scifi city with lots of greenery?"

A 3D rendered pig with wings and a top hat flying over a futuristic sci-fi city filled with greenery

Known Issues

When using this MCP server with Claude Desktop Host:

1. Performance Issues: Using transform_image_from_encoded may take significantly longer to process compared to other methods. This is due to the overhead of transferring large base64-encoded image data through the MCP protocol.

2. Path Resolution Problems: There may be issues with correctly resolving image paths when using Claude Desktop Host. The host application might not properly interpret the returned file paths, making it difficult to access the generated images.

For the best experience, consider using alternative MCP clients or the transform_image_from_file method when possible.

2. transform_image_from_encoded

Transforms an existing image based on a text prompt using base64-encoded image data.

transform_image_from_encoded(encoded_image: str, prompt: str) -> Tuple[bytes, str]

Parameters:

• encoded_image: Base64 encoded image data with format header (must be in format: "data:image/[format];base64,[data]")
• prompt: Text description of how you want to transform the image

Returns:

• A tuple containing:
  • Raw transformed image data (bytes)
  • Path to the saved transformed image file (str)

Example:

• "Add snow to this landscape"
• "Change the background to a beach"

3. transform_image_from_file

Transforms an existing image file based on a text prompt.

transform_image_from_file(image_file_path: str, prompt: str) -> Tuple[bytes, st

... [View full README on GitHub](https://github.com/qhdrl12/mcp-server-gemini-image-generator#readme)