Imagegen-mcp-d3: DALL-E 3-based MCP Server for Image Gen & File Mgmt

Imagegen MCP D3

An MCP server based on DALL-E 3, providing high-quality image generation functions, supporting multiple size, quality, and style configurations, and having automatic file management and error handling capabilities.

Image and video processing Developer tools #Image Generation #AI Painting #MCP Protocol #DALL-E .JavaScript

rating : 2 points

downloads : 6.5K

update time : 2025-07-24

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What is the DALL·E 3 MCP Server?

This is a server that follows the Model Context Protocol (MCP) standard, allowing AI assistants to generate high-quality images through OpenAI's DALL·E 3 model. Users can generate beautiful pictures through simple text descriptions.

How to use the DALL·E 3 MCP Server?

You just need to provide a text description and a save path, and the server will use DALL·E 3 to generate an image and save it to the specified location. The whole process is simple and intuitive, without complex configuration.

Use Cases

Suitable for scenarios that require rapid generation of high-quality images, such as social media content creation, visual design assistance, educational demonstrations, etc. It is especially suitable for users who need to convert text into visual elements.

Main Features

High-quality Image Generation

Utilize the OpenAI DALL·E 3 model to generate images with high resolution and details.

Flexible Configuration

Support different sizes (1024x1024, 1024x1792, 1792x1024), quality (standard or HD), and styles (vivid or natural).

Automatic File Management

Automatically create directories and save generated images to ensure clear file organization.

Detailed Log Recording

Provide detailed log information for easy debugging and monitoring of the image generation process.

Comprehensive Error Handling

Effectively handle common problems, including missing API keys, parameter errors, etc.

Advantages

Provide high-quality image generation capabilities

Support multiple image size and style options

Easy to integrate into existing workflows

Have a good error handling mechanism

Limitations

Dependent on the OpenAI API, which may involve costs

Require a valid API key to run

Have requirements for network connection

The generation time may be long

How to Use

Install the Server

You can install the server using npm or build it from the source code.

Set the API Key

Set the OpenAI API key in the environment variables or create a.env file.

Run the Server

After starting the server, it will listen for MCP protocol requests and be ready to generate images.

Call the Generation Tool

Use the MCP client to send a request, specifying the prompt and output path to generate an image.

Usage Examples

Social Media Content Creation

Create attractive visual content for social media platforms, such as post pictures or covers.

Educational Demonstration

Create illustrations for teaching materials to help students understand abstract concepts.

Product Design

Design preliminary visual effects for new products for market promotion.

Frequently Asked Questions

What do I need to use this server?

How to handle API key errors?

What should I do if I encounter an error when generating an image?

Can I customize the image size?

How to get better image quality?

Related Resources

Official Documentation

Project homepage, containing complete documentation and source code

MCP Specification

Standard specification document for the Model Context Protocol

OpenAI API Documentation

Official documentation for the OpenAI API

GitHub Actions CI/CD

CI/CD pipeline configuration for the project

NPM Package

Project package page on NPM

🚀 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.

🚀 Quick Start

This MCP server enables LLMs to generate high - quality images with OpenAI's DALL - E 3 model via the 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.

📦 Installation

Using NPX (Recommended)

npx imagegen-mcp-d3

Using NPM

npm install -g imagegen-mcp-d3

From Source

git clone https://github.com/chrisurf/imagegen-mcp-d3.git
cd imagegen-mcp-d3
npm install
npm run build
npm start

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:

export OPENAI_API_KEY="your-openai-api-key-here"

Or create a .env file in your project root:

OPENAI_API_KEY=your-openai-api-key-here

💻 Usage Examples

Basic Usage

With Claude Desktop

Add this server to your Claude Desktop configuration:

{
  "mcpServers": {
    "imagegen-mcp-d3": {
      "command": "npx",
      "args": ["imagegen-mcp-d3"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key-here"
      }
    }
  }
}

With Other MCP Clients

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

Advanced Usage

`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:

{
  "name": "generate_image",
  "arguments": {
    "prompt": "A serene sunset over a mountain lake with pine trees",
    "output_path": "/Users/username/Pictures/sunset_lake.png",
    "size": "1024x1792",
    "quality": "hd",
    "style": "natural"
  }
}

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

Original and revised prompts.
Image URL.
File save location.
Image specifications.
File size.

📚 Documentation

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.

🔧 Technical Details

Development

Setup

git clone https://github.com/chrisurf/imagegen-mcp-d3.git
cd imagegen-mcp-d3
npm install

Available Scripts

npm run dev          # Run in development mode with hot reload
npm run build        # Build for production
npm run start        # Start the built server
npm run test         # Run tests
npm run test:watch   # Run tests in watch mode
npm run test:coverage # Run tests with coverage report
npm run lint         # Run ESLint
npm run lint:fix     # Fix ESLint issues
npm run format       # Format code with Prettier
npm run typecheck    # Run TypeScript type checking

Project Structure

src/
├── index.ts           # Main server implementation
├── types.ts          # TypeScript type definitions
└── __tests__/        # Test files
    └── index.test.ts # Main test suite

Running Tests

# Run all tests
npm test

# Run tests with coverage
npm run test:coverage

# Run tests in watch mode during development
npm run test:watch

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

Fork the repository.
Create a feature branch: git checkout -b feature/amazing-feature.
Make your changes.
Add tests for new functionality.
Ensure all tests pass: npm test.
Commit your changes: git commit -m 'Add amazing feature'.
Push to the branch: git push origin feature/amazing-feature.
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.