AI Image Generation Server with MCP Interface

Name: AI Image Generation Server with MCP Interface
Author: aymec

@aymec

AI Image Generation Server with MCP Interface について

This project provides an HTTP server for image generation using Stable Diffusion, along with a Model Context Protocol (MCP) server that enables AI agents to request image generation.

基本情報

カテゴリ

メディアとデザイン

ライセンス

MIT

ランタイム

python

トランスポート

stdio

公開者

aymec

設定

標準の設定はありません

このサーバーの README には解析可能な MCP 設定ブロックが含まれていません。インストール手順はリポジトリをご確認ください。

リポジトリ

ツール

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概要

What is AI Image Generation Server with MCP Interface?

This project provides a Model Context Protocol (MCP) server with integrated Stable Diffusion image generation capabilities, enabling AI agents to request and receive generated images. It is built for developers who want to add AI-powered image generation to agent workflows such as those using Goose or FastMCP Inspector.

How to use AI Image Generation Server with MCP Interface?

Set up a Python virtual environment (named .venv), activate it, and install the package with pip install -e .. Then set the IMAGE_GEN_DIR environment variable to your target folder and run image-gen-mcp. For testing, use development mode with the FastMCP Inspector (web UI at http://127.0.0.1:6274). Integrate with Goose by adding a StandardIO extension with the command uv run /full/path/to/your/project/.venv/bin/image-gen-mcp and the same environment variable.

Key features of AI Image Generation Server with MCP Interface

Integrated Stable Diffusion for image generation
Model Context Protocol (MCP) interface for AI agents
Returns image URL, dimensions, MIME type, and metadata
Customizable port for the image generation service (default 5000)
Works with Goose extension system
Supports local inference via Ollama (tested with mistral-small3.1) or remote models like GPT-4o

Use cases of AI Image Generation Server with MCP Interface

AI agents autonomously generating images from text prompts
Integrating visual outputs into multi‑step agent workflows (e.g., Goose)
Debugging and testing MCP tools with the FastMCP Inspector web interface
Direct API access for standalone image generation via curl or scripts

FAQ from AI Image Generation Server with MCP Interface

What models does it support?

It uses Stable Diffusion for generation. When integrated with Goose, it works immediately with OpenAI GPT-4o and locally with Ollama using the mistral-small3.1 model (slower than GPT-4o).

How do I stop the services?

Press Ctrl+C in the terminal where the server is running. Both the image generation service and MCP server stop together.

Where are generated images stored?

Images are saved to the folder specified by the IMAGE_GEN_DIR environment variable. A direct HTTP endpoint serves them from that folder.

Can I change the default port?

Yes. Use the --port flag when starting the service, for example: image-gen-mcp --port 5001.

What are the runtime dependencies?

Python, a virtual environment, the MCP package (installed via pip install -e .), and the Stable Diffusion backend bundled in the project. For full agent integration, Goose or another MCP client is needed.