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MCP OpenAI Image Generation Server

by LupinLin1

MCP OpenAI Image Generation Server

🚀 零安装配置! 直接在MCP客户端中使用,无需任何预安装步骤

{ "mcpServers": { "imagegen-mcp": { "command": "npx", "args": ["@lupinlin1/imagegen-mcp", "--models", "dall-e-3"], "env": { "OPENAI_API_KEY": "your_api_key" } } } }

This project provides a server implementation based on the Model Context Protocol (MCP) that acts as a wrapper around OpenAI's Image Generation and Editing APIs (see OpenAI documentation).

Features

  • Exposes OpenAI image generation capabilities through MCP tools.
  • Supports text-to-image generation using models like DALL-E 2, DALL-E 3, and gpt-image-1 (if available/enabled).
  • Supports image-to-image editing using DALL-E 2 and gpt-image-1 (if available/enabled).
  • Configurable via environment variables and command-line arguments.
  • Handles various parameters like size, quality, style, format, etc.
  • Saves generated/edited images to temporary files and returns the path along with the base64 data.

Here's an example of generating an image directly in Cursor using the text-to-image tool integrated via MCP:

🚀 快速安装

方法1: 全局安装 (推荐)

npm install -g @lupinlin1/imagegen-mcp

方法2: 一键安装脚本

# macOS/Linux curl -fsSL https://raw.githubusercontent.com/LupinLin1/imagegen-mcp/main/scripts/install.sh | bash # Windows PowerShell iwr https://raw.githubusercontent.com/LupinLin1/imagegen-mcp/main/scripts/install.ps1 | iex

方法3: 使用 npx (无需安装)

npx @lupinlin1/imagegen-mcp [options]

📖 完整安装指南: 查看 INSTALL.md 获取详细说明

Prerequisites

  • Node.js (v18 or later recommended)
  • npm or yarn
  • An OpenAI API key

🎯 零安装配置 (推荐)

**无需任何预安装步骤!**直接配置即可使用:

Cursor 编辑器

{ "mcpServers": { "imagegen-mcp": { "command": "npx", "args": ["@lupinlin1/imagegen-mcp", "--models", "dall-e-3"], "env": { "OPENAI_API_KEY": "your_openai_api_key_here" } } } }

Claude Desktop

{ "mcpServers": { "imagegen-mcp": { "command": "npx", "args": ["@lupinlin1/imagegen-mcp"], "env": { "OPENAI_API_KEY": "your_openai_api_key_here" } } } }

💡 零安装原理

  • 首次运行: npx 自动下载并缓存包
  • 后续启动: 使用缓存,启动快速
  • 自动更新: 始终使用最新版本
  • 无污染: 不会全局安装任何包

📁 更多配置示例: 查看 examples/mcp-configs/ 目录

Setup

  1. Clone the repository:
    git clone <your-repository-url> cd <repository-directory>
  2. Install dependencies:
    npm install # or yarn install
  3. Configure Environment Variables: Create a .env file in the project root by copying the example:
    cp .env.example .env
    Edit the .env file and add your OpenAI API key:
    OPENAI_API_KEY=your_openai_api_key_here

Building

To build the TypeScript code into JavaScript:

npm run build # or yarn build

This will compile the code into the dist directory.

Running the Server

This section provides details on running the server locally after cloning and setup. For a quick start without cloning, see the Quick Run with npx section.

Using ts-node (for development):

npx ts-node src/index.ts [options]

Using the compiled code:

node dist/index.js [options]

Options:

  • --models <model1> <model2> ...: Specify which OpenAI models the server should allow. If not provided, it defaults to allowing all models defined in src/libs/openaiImageClient.ts (currently gpt-image-1, dall-e-2, dall-e-3).
    • Example using npx (also works for local runs): ... --models gpt-image-1 dall-e-3
    • Example after cloning: node dist/index.js --models dall-e-3 dall-e-2

The server will start and listen for MCP requests via standard input/output (using StdioServerTransport).

MCP Tools

The server exposes the following MCP tools:

text-to-image

Generates an image based on a text prompt.

Parameters:

  • text (string, required): The prompt to generate an image from.
  • model (enum, optional): The model to use (e.g., gpt-image-1, dall-e-2, dall-e-3). Defaults to the first allowed model.
  • size (enum, optional): Size of the generated image (e.g., 1024x1024, 1792x1024). Defaults to 1024x1024. Check OpenAI documentation for model-specific size support.
  • style (enum, optional): Style of the image (vivid or natural). Only applicable to dall-e-3. Defaults to vivid.
  • output_format (enum, optional): Format (png, jpeg, webp). Defaults to png.
  • output_compression (number, optional): Compression level (0-100). Defaults to 100.
  • moderation (enum, optional): Moderation level (low, auto). Defaults to low.
  • background (enum, optional): Background (transparent, opaque, auto). Defaults to auto. transparent requires output_format to be png or webp.
  • quality (enum, optional): Quality (standard, hd, auto, ...). Defaults to auto. hd only applicable to dall-e-3.
  • n (number, optional): Number of images to generate. Defaults to 1. Note: dall-e-3 only supports n=1.

Returns:

  • content: An array containing:
    • A text object containing the path to the saved temporary image file (e.g., /tmp/uuid.png).

image-to-image

Edits an existing image based on a text prompt and optional mask.

Parameters:

  • images (string, required): An array of file paths to local images.
  • prompt (string, required): A text description of the desired edits.
  • mask (string, optional): A file path of mask image (PNG). Transparent areas indicate where the image should be edited.
  • model (enum, optional): The model to use. Only gpt-image-1 and dall-e-2 are supported for editing. Defaults to the first allowed model.
  • size (enum, optional): Size of the generated image (e.g., 1024x1024). Defaults to 1024x1024. dall-e-2 only supports 256x256, 512x512, 1024x1024.
  • output_format (enum, optional): Format (png, jpeg, webp). Defaults to png.
  • output_compression (number, optional): Compression level (0-100). Defaults to 100.
  • quality (enum, optional): Quality (standard, hd, auto, ...). Defaults to auto.
  • n (number, optional): Number of images to generate. Defaults to 1.

Returns:

  • content: An array containing:
    • A text object containing the path to the saved temporary image file (e.g., /tmp/uuid.png).

Development

  • Linting: npm run lint or yarn lint
  • Formatting: npm run format or yarn format (if configured in package.json)

Contributing

Pull Requests (PRs) are welcome! Please feel free to submit improvements or bug fixes.

-
security - not tested
A
license - permissive license
-
quality - not tested

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Enables AI assistants to generate and edit images through OpenAI's DALL-E models via MCP tools. Supports text-to-image generation and image-to-image editing with configurable parameters for size, quality, and style.

  1. Features
    1. 🚀 快速安装
      1. 方法1: 全局安装 (推荐)
      2. 方法2: 一键安装脚本
      3. 方法3: 使用 npx (无需安装)
    2. Prerequisites
      1. 🎯 零安装配置 (推荐)
        1. Cursor 编辑器
        2. Claude Desktop
        3. 💡 零安装原理
      2. Setup
        1. Building
          1. Running the Server
            1. MCP Tools
              1. text-to-image
              2. image-to-image
            2. Development
              1. Contributing

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