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Image Generation MCP Server

@sarthakkimtani

基本情報

カテゴリ

メディアとデザイン

ライセンス

MIT

トランスポート

stdio

作者

sarthakkimtani

Image Generation MCP Server について

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

Image Generation MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "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 のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

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

よくある質問

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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