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DALL-E MCP Server

DALL-E MCP Server

by szabadkai

DALL-E MCP Server

A Model Context Protocol (MCP) server for generating images using OpenAI's DALL-E 3 model. This server enables ChatGPT and other MCP-compatible clients to generate high-quality images from text prompts.

Features

  • DALL-E 3 Integration: Uses OpenAI's latest image generation model

  • Flexible Parameters: Configurable image size, quality, and style

  • Local File Storage: Automatically saves generated images to local filesystem

  • Error Handling: Comprehensive error handling with detailed logging

  • TypeScript: Built with TypeScript for type safety and better development experience

Related MCP server: Imagen MCP Server

Installation

  1. Clone this repository:

git clone <repository-url>
cd dall-e-mcp-server
  1. Install dependencies:

npm install
  1. Set up environment variables:

cp .env.example .env
  1. Edit .env file and add your OpenAI API key:

OPENAI_API_KEY=your_openai_api_key_here
DEFAULT_IMAGE_SIZE=1024x1024
DEFAULT_QUALITY=standard
OUTPUT_DIRECTORY=./generated_images

Usage

Running the Server

Development Mode

npm run dev

Production Mode

npm run build
npm start

Integration with Claude Desktop

Add the server to your Claude Desktop configuration:

macOS/Linux (~/.config/claude/claude_desktop_config.json):

{
  "mcpServers": {
    "dall-e-server": {
      "command": "node",
      "args": ["/path/to/dall-e-mcp-server/dist/index.js"],
      "env": {
        "OPENAI_API_KEY": "your_openai_api_key_here"
      }
    }
  }
}

Windows (%APPDATA%/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "dall-e-server": {
      "command": "node",
      "args": ["C:\\path\\to\\dall-e-mcp-server\\dist\\index.js"],
      "env": {
        "OPENAI_API_KEY": "your_openai_api_key_here"
      }
    }
  }
}

Available Tools

generate_image

Generates an image using DALL-E 3 based on a text prompt.

Parameters:

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

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

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

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

  • filename (optional): Custom filename without extension

Example Usage:

{
  "prompt": "A serene mountain landscape at sunset with a lake",
  "size": "1024x1792",
  "quality": "hd",
  "style": "natural",
  "filename": "mountain_sunset"
}

Response:

{
  "success": true,
  "message": "Image generated successfully",
  "details": {
    "prompt": "A serene mountain landscape at sunset with a lake",
    "size": "1024x1792",
    "quality": "hd",
    "style": "natural",
    "file_path": "/absolute/path/to/generated_images/mountain_sunset.png",
    "file_size": 1048576,
    "timestamp": "2025-01-15T10:30:00.000Z"
  }
}

Configuration

Environment Variables

  • OPENAI_API_KEY: Your OpenAI API key (required)

  • DEFAULT_IMAGE_SIZE: Default image size (default: 1024x1024)

  • DEFAULT_QUALITY: Default quality setting (default: standard)

  • OUTPUT_DIRECTORY: Directory to save generated images (default: ./generated_images)

Image Formats

All images are saved as PNG files with automatic timestamping if no filename is provided.

Development

Project Structure

dall-e-mcp-server/
├── src/
│   └── index.ts          # Main server implementation
├── generated_images/     # Generated images directory
├── dist/                 # Compiled JavaScript
├── package.json
├── tsconfig.json
├── .env.example
└── README.md

Building

npm run build

Development with Watch Mode

npm run watch

Error Handling

The server includes comprehensive error handling:

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

  • API Errors: OpenAI API errors are caught and returned with details

  • File System Errors: Issues with saving images are handled gracefully

  • Invalid Parameters: Input validation with helpful error messages

Pricing

DALL-E 3 API pricing (as of 2025):

  • Standard quality: $0.040 per image (1024×1024), $0.080 per image (1024×1792 or 1792×1024)

  • HD quality: $0.080 per image (1024×1024), $0.120 per image (1024×1792 or 1792×1024)

License

MIT License

Contributing

  1. Fork the repository

  2. Create a feature branch

  3. Make your changes

  4. Add tests if applicable

  5. Submit a pull request

Support

For issues and questions:

  1. Check the error messages in the console

  2. Verify your OpenAI API key is valid

  3. Ensure you have sufficient API credits

  4. Review the MCP client configuration

Changelog

v1.0.0

  • Initial release with DALL-E 3 integration

  • Support for all DALL-E 3 parameters

  • Local file storage

  • Error handling and logging

  • TypeScript implementation

Available Tools

1 tool
generate_imageC

Generate an image using OpenAI's DALL-E 3 model based on a text prompt

Inputs: prompt (required), size, quality, style, +1 more.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    B3.2/5.0

    Scored across 1 tool

    Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'generate_image' has a clear, distinct purpose that cannot be confused with any other tool in the set.

    Naming Consistency5/5

    Since there is only one tool, naming consistency is inherently perfect. The tool name 'generate_image' follows a clear verb_noun pattern, and there are no other tools to compare it against for inconsistency.

    Tool Count2/5

    A single tool is too few for most server purposes, as it limits functionality and can feel thin. While DALL-E's core function is image generation, typical MCP servers benefit from multiple tools (e.g., 3-15) to handle related operations like listing images, editing prompts, or managing settings, making this count borderline insufficient.

    Completeness3/5

    The tool set covers the basic image generation function, but there are notable gaps for a DALL-E server. Missing operations might include listing generated images, editing or deleting images, or handling variations, which could lead to agent workarounds or incomplete workflows in more complex tasks.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

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