MCP Image Generator

A powerful MCP (Model Context Protocol) server that enables AI assistants to generate and edit images using Google's Gemini 2.5 Flash Image API. Seamlessly integrate advanced image generation capabilities into Claude Code, Cursor, and other MCP-compatible AI tools.

✨ Features

AI-Powered Image Generation: Create images from text prompts using Gemini 2.5 Flash Image Preview
Intelligent Prompt Enhancement: Automatically optimizes your prompts using Gemini 2.0 Flash for superior image quality
- Adds photographic and artistic details
- Enriches lighting, composition, and atmosphere descriptions
- Preserves your intent while maximizing generation quality
Image Editing: Transform existing images with natural language instructions
- Context-aware editing that preserves original style
- Maintains visual consistency with source image
Advanced Options:
- Multi-image blending for composite scenes
- Character consistency across generations
- World knowledge integration for accurate context
Multiple Output Formats: PNG, JPEG, WebP support
File Output: Images are saved as files for easy access and integration

🔧 Prerequisites

Node.js 20 or higher
Gemini API Key - Get yours at Google AI Studio
Claude Code or Cursor (or any MCP-compatible AI tool)
Basic terminal/command line knowledge

🚀 Quick Start

1. Get Your Gemini API Key

Get your API key from Google AI Studio

2. MCP Configuration

For Claude Code

claude mcp add mcp-image --env GEMINI_API_KEY=your-api-key --env IMAGE_OUTPUT_DIR=/absolute/path/to/images -- npx -y mcp-image

For Cursor

Add to your Cursor settings:

Global (all projects): ~/.cursor/mcp.json
Project-specific: .cursor/mcp.json in your project root

{
  "mcpServers": {
    "mcp-image": {
      "command": "npx",
      "args": ["-y", "mcp-image"],
      "env": {
        "GEMINI_API_KEY": "your_gemini_api_key_here",
        "IMAGE_OUTPUT_DIR": "/absolute/path/to/images"
      }
    }
  }
}

⚠️ Security Note: Never commit your API key to version control. Keep it secure and use environment-specific configuration.

📁 Path Requirements:

IMAGE_OUTPUT_DIR must be an absolute path (e.g., /Users/username/images, not ./images)
Defaults to ./output in the current working directory if not specified
Directory will be created automatically if it doesn't exist

Optional: Skip Prompt Enhancement

Set SKIP_PROMPT_ENHANCEMENT=true to disable automatic prompt optimization and send your prompts directly to the image generator. Useful when you need full control over the exact prompt wording.

Claude Code:

claude mcp add mcp-image --env GEMINI_API_KEY=your-api-key --env SKIP_PROMPT_ENHANCEMENT=true -- npx -y mcp-image

Cursor: Add "SKIP_PROMPT_ENHANCEMENT": "true" to the env section in your config.

📖 Usage Examples

Once configured, your AI assistant can generate images using natural language:

Basic Image Generation

"Generate a serene mountain landscape at sunset with a lake reflection"

The system automatically enhances this to include rich details about lighting, materials, composition, and atmosphere for optimal results.

Image Editing

"Edit this image to make the person face right"
(with inputImagePath: "/path/to/image.jpg")

Advanced Features

"Generate a portrait of a medieval knight, maintaining character consistency for future variations"
(with maintainCharacterConsistency: true)

🔧 API Reference

`generate_image` Tool

The MCP server exposes a single tool for all image operations. Internally, it uses a two-stage process:

Prompt Optimization: Gemini 2.0 Flash analyzes and enriches your prompt
Image Generation: Gemini 2.5 Flash Image Preview creates the final image

Parameters

Parameter	Type	Required	Description
`prompt`	string	✅	Text description or editing instruction
`inputImagePath`	string	❌	Absolute path to input image for editing
`fileName`	string	❌	Custom filename for output (auto-generated if not specified)
`blendImages`	boolean	❌	Enable multi-image blending
`maintainCharacterConsistency`	boolean	❌	Maintain character appearance across generations
`useWorldKnowledge`	boolean	❌	Use real-world knowledge for context

Response

{
  "type": "resource",
  "resource": {
    "uri": "file:///path/to/generated/image.png",
    "name": "image-filename.png",
    "mimeType": "image/png"
  },
  "metadata": {
    "model": "gemini-2.5-flash-image-preview",
    "processingTime": 5000,
    "timestamp": "2024-01-01T12:00:00.000Z"
  }
}

🛠️ Troubleshooting

Common Issues

"API key not found"

Ensure GEMINI_API_KEY is set in your environment
Verify the API key is valid and has image generation permissions

"Input image file not found"

Use absolute file paths, not relative paths
Ensure the file exists and is accessible
Supported formats: PNG, JPEG, WebP (max 10MB)

"No image data found in Gemini API response"

Try rephrasing your prompt with more specific details
Ensure your prompt is appropriate for image generation
Check if your API key has sufficient quota

Performance Tips

Image generation: 30-60 seconds typical (includes prompt optimization)
Image editing: 15-45 seconds typical (includes context analysis)
Simple prompts work great - the AI automatically adds professional details
Complex prompts are preserved and further enhanced
Consider enabling useWorldKnowledge for historical or factual subjects

💰 Usage Notes

This MCP server uses the paid Gemini API for both prompt optimization and image generation
- Gemini 2.0 Flash for intelligent prompt enhancement (minimal token usage)
- Gemini 2.5 Flash Image Preview for actual image generation
Check current pricing and rate limits at Google AI Studio
Monitor your API usage to avoid unexpected charges
The prompt optimization step adds minimal cost while significantly improving output quality

📄 License

MIT License - see LICENSE for details.

Need help? Open an issue or check the troubleshooting section above.

MCP Image Generator