DALL-E 3 MCP Server

A Model Context Protocol (MCP) server that provides DALL-E 3 image generation capabilities. This server allows LLMs to generate high-quality images using OpenAI's DALL-E 3 model through the standardized MCP interface.

Features

• 🎨 High-Quality Image Generation: Uses DALL-E 3 for state-of-the-art image creation

• 🔧 Flexible Configuration: Support for different sizes, quality levels, and styles

• 📁 Automatic File Management: Handles directory creation and file saving

• 🛡️ Robust Error Handling: Comprehensive error handling with detailed feedback

• 📊 Detailed Logging: Comprehensive logging for debugging and monitoring

• 🚀 TypeScript: Fully typed for better development experience

• 🧪 Well Tested: Comprehensive test suite with high coverage

Related MCP server: OpenAI MCP

Installation

Using NPX (Recommended)

Using NPM

From Source

Prerequisites

• Node.js: Version 18.0.0 or higher

• OpenAI API Key: You need a valid OpenAI API key with DALL-E 3 access

Configuration

Environment Variables

Set your OpenAI API key as an environment variable:

Or create a .env file in your project root:

Usage

With Claude Desktop

Add this server to your Claude Desktop configuration:

With Other MCP Clients

The server implements the standard MCP protocol and can be used with any compatible client.

Available Tools

generate_image

Generates an image using DALL-E 3 and saves it to the specified location.

Parameters:

• prompt (required): Text description of the image to generate

• output_path (required): Full file path where the image should be saved

• size (optional): Image dimensions - "1024x1024", "1024x1792", or "1792x1024" (default: "1024x1024")

• quality (optional): Image quality - "standard" or "hd" (default: "hd")

• style (optional): Image style - "vivid" or "natural" (default: "vivid")

Example:

Response:

The tool returns detailed information about the generated image, including:

• Original and revised prompts

• Image URL

• File save location

• Image specifications

• File size

API Reference

Image Sizes

• Square: 1024x1024 - Perfect for social media and general use

• Portrait: 1024x1792 - Great for mobile wallpapers and vertical displays

• Landscape: 1792x1024 - Ideal for desktop wallpapers and horizontal displays

Quality Options

• Standard: Faster generation, good quality

• HD: Higher quality with more detail (recommended)

Style Options

• Vivid: More dramatic and artistic interpretations

• Natural: More realistic and natural-looking results

Development

Setup

Available Scripts

Project Structure

Running Tests

Error Handling

The server provides comprehensive error handling for common scenarios:

• Missing API Key: Clear error message when OPENAI_API_KEY is not set

• Invalid Parameters: Validation errors for required and optional parameters

• API Errors: Detailed error messages from the OpenAI API

• File System Errors: Handling of directory creation and file writing issues

• Network Errors: Graceful handling of network connectivity issues

Logging

The server provides detailed logging for monitoring and debugging:

• Request initiation and parameters

• API communication status

• Image generation progress

• File saving confirmation

• Error details and stack traces

Contributing

We welcome contributions! Please see our Contributing Guidelines for details.

Development Workflow

1. Fork the repository

2. Create a feature branch: git checkout -b feature/amazing-feature

3. Make your changes

4. Add tests for new functionality

5. Ensure all tests pass: npm test

6. Commit your changes: git commit -m 'Add amazing feature'

7. Push to the branch: git push origin feature/amazing-feature

8. Open a Pull Request

CI/CD

This project uses GitHub Actions for continuous integration and deployment:

• Testing: Automated testing on multiple Node.js versions (18, 20, 22)

• Code Quality: ESLint, Prettier, and TypeScript checks

• Security: Dependency vulnerability scanning

• Publishing: Automatic NPM publishing on release

• Coverage: Local code coverage reporting

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

• Issues: GitHub Issues

• Discussions: GitHub Discussions

• Email: Open an issue for support

Changelog

See CHANGELOG.md for a detailed history of changes.

Related Projects

• Model Context Protocol - The official MCP specification

• MCP TypeScript SDK - TypeScript SDK for MCP

• Claude Desktop - AI assistant that supports MCP servers

Acknowledgments

• OpenAI for the DALL-E 3 API

• Anthropic for the Model Context Protocol specification

• The MCP community for tools and documentation High-performance MCP for generating images using DALL·E 3 – optimized for fast, scalable, and customizable inference workflows.