create-image-mcp
An MCP server that generates and edits images using OpenAI's GPT Image model, allowing users to create images from text descriptions and edit existing images through natural language.
README
Create Image MCP Server
A Model Context Protocol (MCP) server that generates and edits images using OpenAI's GPT Image model (gpt-image-1.5). This server enables Claude Desktop, Claude Code, and other MCP clients to create images from text descriptions and edit existing images.
Features
- Text-to-image generation via OpenAI GPT Image model
- Image editing and style transfer with input image support
- Configurable size, quality, and output format
- Transparent background support
- Multiple image variations in a single request
- Images saved to disk with text-only responses (no base64 bloat)
- Retry with exponential backoff for transient failures
Prerequisites
- Node.js >= 20.0.0
- OpenAI API Key
Installation
Option 1: NPM Global Install (Recommended)
npm install -g @gpriday/create-image-mcp
The create-image-mcp command will be available globally.
Option 2: Local Development Install
git clone https://github.com/gpriday/create-image-mcp.git
cd create-image-mcp
npm install
Configuration
Create a .env file in your project root or home directory (~/.env):
OPENAI_API_KEY=your_api_key_here
You can get an OpenAI API key from OpenAI Platform.
For local development, validate your configuration with:
npm run check-env
The server will automatically load .env from:
- Current working directory (
.env) - Home directory (
~/.env) as fallback - Or use environment variables directly
Usage
Run the MCP Server
If installed globally:
create-image-mcp
If running locally:
npm start
The server runs on stdio and communicates via JSON-RPC 2.0.
Test the Server
npm test # Unit tests
npm run test:integration # Integration test with live API
npm run test:all # All tests
Available Tools
create_image
Generate or edit images using OpenAI GPT Image.
Use when: user says "create an image", "generate a picture", "draw", "make an illustration", "edit an image", "transform a photo", or any visual content creation request.
Parameters:
| Parameter | Required | Type | Default | Description |
|---|---|---|---|---|
prompt |
Yes | string | - | Image description or editing instructions (1-32,000 chars) |
output_file |
Yes | string | - | File path to save the generated image |
input_images |
No | array | - | File paths to input images for editing (supports PNG/JPEG/WebP/GIF, max 20MB each) |
size |
No | enum | 1024x1024 |
1024x1024, 1024x1536, 1536x1024, auto |
quality |
No | enum | auto |
low, medium, high, auto |
background |
No | enum | auto |
transparent, opaque, auto |
number_of_images |
No | integer | 1 |
Number of variations (1-4) |
output_mime_type |
No | enum | image/png |
image/png, image/jpeg, image/webp |
Examples:
Generate a simple image:
{
"name": "create_image",
"arguments": {
"prompt": "A serene mountain landscape at sunset with golden light",
"output_file": "./landscape.png"
}
}
Generate with specific settings:
{
"name": "create_image",
"arguments": {
"prompt": "A futuristic city skyline with flying cars, cyberpunk style",
"output_file": "./cyberpunk-city.png",
"size": "1536x1024",
"quality": "high",
"number_of_images": 2
}
}
Generate with transparent background:
{
"name": "create_image",
"arguments": {
"prompt": "A minimalist flat vector logo of an owl",
"output_file": "./logo.png",
"background": "transparent"
}
}
Edit an existing image:
{
"name": "create_image",
"arguments": {
"prompt": "Change the background to a beach scene",
"input_images": ["./photo.jpg"],
"output_file": "./edited-photo.png"
}
}
Style transfer:
{
"name": "create_image",
"arguments": {
"prompt": "Make this image look like a watercolor painting",
"input_images": ["./source.png"],
"output_file": "./watercolor.png"
}
}
Response Format:
The tool saves images to disk and returns a text-only response:
Image saved to: ./landscape.png (245.3 KB, image/png)
For multiple images, files are numbered:
Image saved to: ./cyberpunk-city_1.png (312.1 KB, image/png)
Image saved to: ./cyberpunk-city_2.png (298.7 KB, image/png)
Integration with Claude Desktop
Add this server to your Claude Desktop configuration.
If Installed Globally (Recommended)
macOS
Edit ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"create-image": {
"command": "create-image-mcp",
"env": {
"OPENAI_API_KEY": "your_api_key_here"
}
}
}
}
Windows
Edit %APPDATA%\Claude\claude_desktop_config.json:
{
"mcpServers": {
"create-image": {
"command": "create-image-mcp",
"env": {
"OPENAI_API_KEY": "your_api_key_here"
}
}
}
}
Linux
Edit ~/.config/Claude/claude_desktop_config.json:
{
"mcpServers": {
"create-image": {
"command": "create-image-mcp",
"env": {
"OPENAI_API_KEY": "your_api_key_here"
}
}
}
}
If Running Locally
macOS
Edit ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"create-image": {
"command": "node",
"args": ["/path/to/create-image-mcp/src/index.js"],
"env": {
"OPENAI_API_KEY": "your_api_key_here"
}
}
}
}
Windows
Edit %APPDATA%\Claude\claude_desktop_config.json:
{
"mcpServers": {
"create-image": {
"command": "node",
"args": ["C:\\path\\to\\create-image-mcp\\src\\index.js"],
"env": {
"OPENAI_API_KEY": "your_api_key_here"
}
}
}
}
Linux
Edit ~/.config/Claude/claude_desktop_config.json:
{
"mcpServers": {
"create-image": {
"command": "node",
"args": ["/path/to/create-image-mcp/src/index.js"],
"env": {
"OPENAI_API_KEY": "your_api_key_here"
}
}
}
}
After updating the configuration, restart Claude Desktop.
Integration with Claude Code
Option 1: Project-Level mcp.json (Recommended)
Add an mcp.json file to your project root. This is the simplest approach and works automatically when Claude Code opens the project.
Note: If
OPENAI_API_KEYis already set in your shell environment (e.g. in~/.zshrc,~/.bashrc, or~/.env), you can omit theenvfield entirely.
If installed globally:
{
"mcpServers": {
"create-image": {
"command": "create-image-mcp",
"env": {
"OPENAI_API_KEY": "your_api_key_here"
}
}
}
}
If running locally:
{
"mcpServers": {
"create-image": {
"command": "node",
"args": ["/path/to/create-image-mcp/src/index.js"],
"env": {
"OPENAI_API_KEY": "your_api_key_here"
}
}
}
}
Option 2: CLI Command
For current project only:
claude mcp add --scope project create-image -e OPENAI_API_KEY=your_api_key_here -- create-image-mcp
For your user (available in all projects):
claude mcp add --scope user create-image -e OPENAI_API_KEY=your_api_key_here -- create-image-mcp
Verify the server is running:
claude mcp list
Integration with OpenAI Codex
Add the MCP server using the codex mcp add command or by editing ~/.codex/config.toml.
Using CLI (Recommended)
If installed globally:
codex mcp add create-image --env OPENAI_API_KEY=your_api_key_here -- create-image-mcp
If running locally:
codex mcp add create-image --env OPENAI_API_KEY=your_api_key_here -- node /path/to/create-image-mcp/src/index.js
Manual Configuration
Edit ~/.codex/config.toml:
[mcp.create-image]
command = "create-image-mcp"
env = ["OPENAI_API_KEY=your_api_key_here"]
Development
Dependency Management
- Semver Ranges: Dependencies use caret (
^) ranges for automatic patch/minor security updates - Lockfile:
package-lock.jsonis committed for reproducible builds - CI/CD: Use
npm ci(notnpm install) to enforce lockfile versions - Security: Run
npm run security:auditregularly
Project Structure
create-image/
├── src/
│ └── index.js # Main MCP server
├── scripts/
│ └── check-env.js # Environment validation
├── test/
│ ├── unit/
│ │ ├── tool-handler.test.js # Unit tests
│ │ └── tool-description.test.js # Schema tests
│ └── test-create-image-mcp.js # Integration tests
├── package.json
├── package-lock.json # Committed for reproducibility
├── .env # API key (git-ignored)
├── .env.example # API key template
├── .gitignore
├── LICENSE
└── README.md
Scripts
Development:
npm start- Start the MCP server (auto-runs environment validation)npm test- Run unit testsnpm run test:integration- Run integration testsnpm run test:all- Run all testsnpm run dev- Run server with auto-reload
Environment & Security:
npm run check-env- Validate environment configurationnpm run security:audit- Check for security vulnerabilitiesnpm run security:fix- Auto-fix security issuesnpm run security:update- Update dependencies and audit
Error Handling
The server provides categorized error handling:
- Input Validation: Parameters validated for presence, type, length, and enum membership
- [AUTH_ERROR]: Missing or invalid API keys
- [QUOTA_ERROR]: API quota, rate limit, or billing errors
- [TIMEOUT_ERROR]: Request timeout errors
- [SAFETY_ERROR]: Content blocked by safety filters or content policy violations
- [API_ERROR]: General API errors
- Retry Logic: Transient failures retried with exponential backoff (up to 3 attempts)
- Process Stability: Unhandled rejections and exceptions trigger clean shutdown
License
MIT
Contributing
Contributions welcome! Please open an issue or PR.
Support
For issues or questions:
- Check the MCP documentation
- Review OpenAI API docs
- Open an issue in this repository
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