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Image Generation MCP Server

@sarthakkimtani

代码仓库

基本信息

分类

媒体与设计

许可证

MIT

传输方式

stdio

作者

sarthakkimtani

关于 Image Generation MCP Server

MCP server enabling Image Generation for LLMs, built in Python and integrated with Together AI.

#python#ai#mcp#llms#claude-ai

Image Generation MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "image-gen": {
      "command": "uv",
      "args": [
        "--directory",
        "/ABSOLUTE/PATH/TO/image-gen/",
        "run",
        "image-gen"
      ],
      "env": {
        "TOGETHER_AI_API_KEY": "<API KEY>"
      }
    }
  }
}

Image Generation MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Image Generation MCP Server?

A Model Context Protocol (MCP) server that enables seamless generation of high-quality images via Together AI. It provides a standardized interface to specify image generation parameters for MCP-compatible clients.

How to use Image Generation MCP Server?

Install using uv and configure in your MCP client (e.g., Claude Desktop) by adding a server entry with the command uv --directory /ABSOLUTE/PATH/TO/image-gen/ run image-gen and the required TOGETHER_AI_API_KEY environment variable. Once connected, call the generate_image tool with a descriptive prompt and optional width, height, and model parameters.

Key features of Image Generation MCP Server

  • High-quality image generation via the Flux.1 Schnell model
  • Customizable output dimensions (width and height)
  • Clear error handling for prompt validation and API issues
  • Easy integration with MCP-compatible clients
  • Support for specifying an exact Together AI model with automatic fallback

Use cases of Image Generation MCP Server

  • Generate images from descriptive text prompts for content creation
  • Specify custom dimensions to match project layout requirements
  • Integrate image generation into existing MCP-based workflows and tools

常见问题

1

What model does the server use by default?

The default model is `black-forest-labs/FLUX.1-schnell`. You can override it with any Together AI model name via the `model` parameter.

2

What are the prerequisites for running the server?

You need Python 3.12 or higher, the `httpx` and `mcp` packages, and a valid Together AI API key.

3

How do I configure the API key?

Set the `TOGETHER_AI_API_KEY` environment variable in your MCP client configuration (e.g., `claude_desktop_config.json`).

4

What tools does the server provide?

It provides one tool: `generate_image`, which accepts a `prompt` (required), and optional `width`, `height`, and `model` parameters.

5

Can I specify the image dimensions?

Yes, you can optionally set `width` and `height` in pixels when calling `generate_image`.

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