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Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

This server doesn't publish a one-line install command. Follow the setup in the source repository.

Summary

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.md

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: ``bash npm run check-env ``

The server will automatically load .env from:

  1. Current working directory (.env)
  2. Home directory (~/.env) as fallback
  3. Or use environment variables directly

Usage

Run the MCP Server

If installed globally: ``bash create-image-mcp ``

If running locally: ``bash 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: ``json { "name": "create_image", "arguments": { "prompt": "A serene mountain landscape at sunset with golden light", "output_file": "./landscape.png" } } ``

Generate with specific settings: ``json { "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: ``json { "name": "create_image", "arguments": { "prompt": "A minimalist flat vector logo of an owl", "output_file": "./logo.png", "background": "transparent" } } ``

Edit an existing image: ``json { "name": "create_image", "arguments": { "prompt": "Change the background to a beach scene", "input_images": ["./photo.jpg"], "output_file": "./edited-photo.png" } } ``

Style transfer: ``json { "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_KEY is already set in your shell environment (e.g. in ~/.zshrc, ~/.bashrc, or ~/.env), you can omit the env field entirely.

If installed globally: ``json { "mcpServers": { "create-image": { "command": "create-image-mcp", "env": { "OPENAI_API_KEY": "your_api_key_here" } } } } ``

If running locally: ``json { "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: ``bash 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): ``bash claude mcp add --scope user create-image -e OPENAI_API_KEY=your_api_key_here -- create-image-mcp ``

Verify the server is running: ``bash 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: ``bash codex mcp add create-image --env OPENAI_API_KEY=your_api_key_here -- create-image-mcp ``

If running locally: ``bash 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.json is committed for reproducible builds
  • CI/CD: Use npm ci (not npm install) to enforce lockfile versions
  • Security: Run npm run security:audit regularly

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 tests
  • npm run test:integration - Run integration tests
  • npm run test:all - Run all tests
  • npm run dev - Run server with auto-reload

Environment & Security:

  • npm run check-env - Validate environment configuration
  • npm run security:audit - Check for security vulnerabilities
  • npm run security:fix - Auto-fix security issues
  • npm 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:

  1. Check the MCP documentation
  2. Review OpenAI API docs
  3. Open an issue in this repository

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