mcp-gemini-image
An MCP server that provides image generation capabilities using Google's Gemini 2.5 Flash Image Preview model.
README
mcp-gemini-image
An MCP (Model Context Protocol) server that provides image generation capabilities using Google's Gemini 2.5 Flash Image Preview model.
Features
- Text-to-Image Generation: Generate images from text prompts
- Image-to-Image Generation: Transform existing images with text guidance
- Resource Management: Access generated images through MCP resources
- Automatic Cleanup: Auto-deletes images older than 8 hours on startup
- Security: Built-in rate limiting, input validation, and file size limits
Installation
Prerequisites
You'll need a Google Gemini API key. Get one from Google AI Studio.
Option 1: Install with Claude Code (Recommended)
-
Clone or download this repository to your local machine
-
Add the MCP server using the Claude CLI:
macOS/Linux:
claude mcp add mcp-gemini-image --env GEMINI_API_KEY=your-api-key-here \
-- node /absolute/path/to/mcp-gemini-image/index.js
Windows:
claude mcp add mcp-gemini-image --env GEMINI_API_KEY=your-api-key-here -- cmd /c node C:\absolute\path\to\mcp-gemini-image\index.js
- Restart Claude Code to load the server
Note: The -- separator is required to separate Claude CLI flags from the server command.
Option 2: Manual Configuration
Add this configuration to your Claude Desktop config file:
MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"mcp-gemini-image": {
"command": "node",
"args": ["/absolute/path/to/mcp-gemini-image/index.js"],
"env": {
"GEMINI_API_KEY": "your-api-key-here"
}
}
}
}
Option 3: Install with Gemini Code Assist
-
Clone or download this repository to your local machine
-
Open your Gemini settings file:
- VS Code:
~/.gemini/settings.json - IntelliJ: Create
mcp.jsonin your IDE's configuration directory
- VS Code:
-
Add the server configuration:
{
"mcpServers": {
"mcp-gemini-image": {
"command": "node",
"args": ["/absolute/path/to/mcp-gemini-image/index.js"],
"env": {
"GEMINI_API_KEY": "your-api-key-here"
}
}
}
}
- Restart your IDE to load the MCP server
Option 4: Install with OpenAI Codex
-
Clone or download this repository to your local machine
-
Open your Codex config file:
~/.codex/config.toml -
Add the server configuration:
[mcp_servers.mcp-gemini-image]
command = "node"
args = ["/absolute/path/to/mcp-gemini-image/index.js"]
env = { "GEMINI_API_KEY" = "your-api-key-here" }
- Restart Codex to load the MCP server
Option 5: Install from NPM (if published)
npm install -g mcp-gemini-image
Then configure in your MCP client:
{
"mcpServers": {
"mcp-gemini-image": {
"command": "mcp-gemini-image",
"env": {
"GEMINI_API_KEY": "your-api-key-here"
}
}
}
}
Usage
Once configured, the server provides two tools:
generate_image
Generate an image from a text prompt.
Parameters:
prompt(string, required): Text description of the image to generateinput_image(string, optional): Base64-encoded input image for image-to-image generationinput_image_mime_type(string, optional): MIME type of input image (default: "image/png")
Example:
{
"prompt": "A serene mountain landscape at sunset",
"input_image": "base64encodeddata...",
"input_image_mime_type": "image/jpeg"
}
cleanup_images
Delete generated images based on age.
Parameters:
max_age_hours(number, optional): Delete only images older than this many hours. If not specified, deletes all images.
Example:
{
"max_age_hours": 24
}
Resources
Generated images are exposed as MCP resources with URIs in the format:
gemini-image:///<filename>
These resources can be read by MCP clients to access the generated images.
Security Features
- Rate Limiting: 10 requests per minute
- Input Validation: Validates prompts and base64 data
- File Size Limits:
- Generated images: 10MB max
- Input images: 20MB max (base64)
- Prompts: 10,000 characters max
- Path Traversal Protection: Validates all file paths
- Extension Whitelist: Only allows png, jpeg, jpg, webp, gif
- Automatic Cleanup: Removes images older than 8 hours on startup
Development
Run the server directly:
npm start
The server uses stdio transport and is designed to be invoked by MCP clients.
File Structure
.
├── index.js # Main server implementation
├── package.json # NPM configuration
├── .gitignore # Excludes generated_images/
├── CLAUDE.md # Claude Code guidance
└── generated_images/ # Auto-generated images (created automatically)
Troubleshooting
"GEMINI_API_KEY environment variable is required"
Make sure you've set the GEMINI_API_KEY environment variable in your MCP client configuration.
"Rate limit exceeded"
The server limits requests to 10 per minute. Wait a moment before trying again.
"Invalid or unsupported image type"
Only png, jpeg, jpg, webp, and gif formats are supported.
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.