hlee/gemini-imagen-mcp
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The Gemini Imagen MCP Server is a TypeScript-based server that leverages Google's Gemini Imagen API to provide image generation capabilities through the Model Context Protocol.
Gemini Imagen MCP Server
A TypeScript-based MCP server that provides image generation capabilities using Google's Gemini Imagen API. This server allows you to generate high-quality images with customizable parameters through the Model Context Protocol.
Features
Tools
generate_image- Generate images using Google Gemini Imagen- prompt (required): Text description for image generation
- numberOfImages (optional): Number of images to generate (1-4, default: 1)
- aspectRatio (optional): Image aspect ratio (default: "9:16")
- sampleImageSize (optional): Image resolution (default: "2K")
- personGeneration (optional): Control person generation (default: "allow_adult")
Parameter Options
aspectRatio
Controls the aspect ratio of generated images:
"1:1"- Square format"3:4"- Portrait format"4:3"- Landscape format"9:16"- Vertical format (default)"16:9"- Horizontal format
sampleImageSize
Controls the resolution of generated images (Standard and Ultra models only):
"1K"- Lower resolution"2K"- Higher resolution (default)
personGeneration
Controls whether the model can generate images of people:
"dont_allow"- Block generation of people"allow_adult"- Generate adults only (default)"allow_all"- Generate adults and children
Usage Examples
Basic Usage (Default Settings)
{
"prompt": "A beautiful sunset over mountains"
}
This will use default settings:
- aspectRatio: "9:16"
- sampleImageSize: "2K"
- personGeneration: "allow_adult"
Custom Parameters
{
"prompt": "A cute cat playing with a ball",
"aspectRatio": "1:1",
"sampleImageSize": "1K",
"personGeneration": "dont_allow",
"numberOfImages": 2
}
Portrait Photography
{
"prompt": "Professional headshot of a business person",
"aspectRatio": "3:4",
"sampleImageSize": "2K",
"personGeneration": "allow_adult"
}
Landscape Photography
{
"prompt": "Panoramic view of a mountain range at dawn",
"aspectRatio": "16:9",
"sampleImageSize": "2K"
}
Development
Install dependencies:
npm install
Build the server:
npm run build
For development with auto-rebuild:
npm run watch
Installation
Method 1: Using npx (Recommended)
Add the server config to your MCP client:
On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"gemini-imagen": {
"command": "npx",
"args": ["/path/to/gemini-imagen-server/build/index.js"],
"env": {
"GEMINI_API_KEY": "YOUR_GEMINI_API_KEY"
}
}
}
}
Method 2: Using node directly
{
"mcpServers": {
"gemini-imagen": {
"command": "node",
"args": ["/path/to/gemini-imagen-server/build/index.js"],
"env": {
"GEMINI_API_KEY": "YOUR_GEMINI_API_KEY"
}
}
}
}
Configuration
API Key Setup
The GEMINI_API_KEY can be provided in two ways:
- Environment variable in MCP config (recommended):
{
"mcpServers": {
"gemini-imagen": {
"command": "npx",
"args": ["/path/to/gemini-imagen-server/build/index.js"],
"env": {
"GEMINI_API_KEY": "YOUR_GEMINI_API_KEY"
}
}
}
}
- System environment variable:
export GEMINI_API_KEY="YOUR_GEMINI_API_KEY"
Getting a Gemini API Key
- Go to Google AI Studio
- Sign in with your Google account
- Click "Get API Key"
- Create a new API key
- Copy the key and use it in your configuration
Output
Generated images are saved to /tmp/ with timestamped filenames:
- Format:
generated_image_[timestamp]_[index].png - Example:
generated_image_1758733788860_0.png
Debugging
Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector:
npm run inspector
The Inspector will provide a URL to access debugging tools in your browser.
Error Handling
The server includes comprehensive error handling:
- Invalid parameters are validated and rejected
- API errors are caught and reported with helpful messages
- Missing API keys are detected and reported clearly
- Network issues are handled gracefully
License
This project is licensed under the MIT License.