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Together Flux 生成器

一个模型上下文协议服务器,通过Together AI使用Flux.1 Schnell模型实现高质量图像生成,并且参数可定制。

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README

Image Generation MCP Server

A Model Context Protocol (MCP) server that enables seamless generation of high-quality images using the Flux.1 Schnell model via Together AI. This server provides a standardized interface to specify image generation parameters.

Image Generation Server MCP server

Features

  • High-quality image generation powered by the Flux.1 Schnell model
  • Support for customizable dimensions (width and height)
  • Clear error handling for prompt validation and API issues
  • Easy integration with MCP-compatible clients
  • Optional image saving to disk in PNG format

Installation

npm install together-mcp

Or run directly:

npx together-mcp@latest

Configuration

Add to your MCP server configuration:

Configuration Example
{
  "mcpServers": {
    "together-image-gen": {
      "command": "npx",
      "args": ["together-mcp@latest -y"],
      "env": {
        "TOGETHER_API_KEY": "<API KEY>"
      }
    }
  }
}

Usage

The server provides one tool: generate_image

Using generate_image

This tool has only one required parameter - the prompt. All other parameters are optional and use sensible defaults if not provided.

Parameters

{
  // Required
  prompt: string;          // Text description of the image to generate

  // Optional with defaults
  model?: string;          // Default: "black-forest-labs/FLUX.1-schnell-Free"
  width?: number;          // Default: 1024 (min: 128, max: 2048)
  height?: number;         // Default: 768 (min: 128, max: 2048)
  steps?: number;          // Default: 1 (min: 1, max: 100)
  n?: number;             // Default: 1 (max: 4)
  response_format?: string; // Default: "b64_json" (options: ["b64_json", "url"])
  image_path?: string;     // Optional: Path to save the generated image as PNG
}

Minimal Request Example

Only the prompt is required:

{
  "name": "generate_image",
  "arguments": {
    "prompt": "A serene mountain landscape at sunset"
  }
}

Full Request Example with Image Saving

Override any defaults and specify a path to save the image:

{
  "name": "generate_image",
  "arguments": {
    "prompt": "A serene mountain landscape at sunset",
    "width": 1024,
    "height": 768,
    "steps": 20,
    "n": 1,
    "response_format": "b64_json",
    "model": "black-forest-labs/FLUX.1-schnell-Free",
    "image_path": "/path/to/save/image.png"
  }
}

Response Format

The response will be a JSON object containing:

{
  "id": string,        // Generation ID
  "model": string,     // Model used
  "object": "list",
  "data": [
    {
      "timings": {
        "inference": number  // Time taken for inference
      },
      "index": number,      // Image index
      "b64_json": string    // Base64 encoded image data (if response_format is "b64_json")
      // OR
      "url": string        // URL to generated image (if response_format is "url")
    }
  ]
}

If image_path was provided and the save was successful, the response will include confirmation of the save location.

Default Values

If not specified in the request, these defaults are used:

  • model: "black-forest-labs/FLUX.1-schnell-Free"
  • width: 1024
  • height: 768
  • steps: 1
  • n: 1
  • response_format: "b64_json"

Important Notes

  1. Only the prompt parameter is required
  2. All optional parameters use defaults if not provided
  3. When provided, parameters must meet their constraints (e.g., width/height ranges)
  4. Base64 responses can be large - use URL format for larger images
  5. When saving images, ensure the specified directory exists and is writable

Prerequisites

  • Node.js >= 16
  • Together AI API key
    1. Sign in at api.together.xyz
    2. Navigate to API Keys settings
    3. Click "Create" to generate a new API key
    4. Copy the generated key for use in your MCP configuration

Dependencies

{
  "@modelcontextprotocol/sdk": "0.6.0",
  "axios": "^1.6.7"
}

Development

Clone and build the project:

git clone https://github.com/manascb1344/together-mcp-server
cd together-mcp-server
npm install
npm run build

Available Scripts

  • npm run build - Build the TypeScript project
  • npm run watch - Watch for changes and rebuild
  • npm run inspector - Run MCP inspector

Contributing

Contributions are welcome! Please follow these steps:

  1. Fork the repository
  2. Create a new branch (feature/my-new-feature)
  3. Commit your changes
  4. Push the branch to your fork
  5. Open a Pull Request

Feature requests and bug reports can be submitted via GitHub Issues. Please check existing issues before creating a new one.

For significant changes, please open an issue first to discuss your proposed changes.

License

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

help

运行方式说明

cloud

托管运行

托管运行通常表示这个 MCP Server 由服务方环境承载,用户一般按页面提供的连接方式或授权流程接入,不需要在本地长期启动一个 MCP 进程

  1. 打开服务方连接页
  2. 完成授权或复制端点
  3. 在 MCP 客户端中连接
terminal

本地运行 / 其它方式

本地运行通常需要用户在自己的电脑或服务器上安装依赖,把 server_config 复制到 MCP 客户端,并按 env_schema 补齐环境变量、密钥或其它配置

  1. 复制 server_config
  2. 安装所需依赖
  3. 补齐环境变量后重启客户端