MCP Server for ModelScope Qwen-Image text-to-image generation
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# ModelScope Image MCP Server English | [中文](README-zh.md) An MCP (Model Context Protocol) server for generating images via the ModelScope image generation API. This server provides seamless integration with AI assistants, enabling them to create images through natural language prompts with robust async processing and local file management. > IMPORTANT: Earlier drafts of this README mentioned features like returning base64 data, negative prompts, and additional parameters. The current released code (see `src/modelscope_image_mcp/server.py`) implements a focused minimal feature set: one tool `generate_image` that submits an async task and saves the resulting image locally. Planned / upcoming features are listed in the roadmap below. ## Current Features - Asynchronous image generation using ModelScope async task API - Periodic task status polling (every 5 seconds, up to 2 minutes) - Saves the first generated image to a local file - Returns task status and image URL to the MCP client - Robust error handling + timeout messaging - Simple one-command start with `uvx` ## Environment Variable The server reads your credential from: ``` MODELSCOPE_SDK_TOKEN ``` If it is missing, the server will raise an error. Obtain a token from: https://modelscope.cn/my/myaccesstoken ### Set on Windows (cmd): ``` set MODELSCOPE_SDK_TOKEN=your_token_here ``` PowerShell: ``` $env:MODELSCOPE_SDK_TOKEN="your_token_here" ``` Unix/macOS bash/zsh: ``` export MODELSCOPE_SDK_TOKEN=your_token_here ``` ## Installation & MCP Client Configuration You can register the server directly in an MCP-compatible client (e.g. Claude Desktop) without a prior manual install thanks to `uvx`. ### Option 1: PyPI (Recommended once published) ```jsonc { "mcpServers": { "modelscope-image": { "command": "uvx", "args": ["modelscope-image-mcp"], "env": { "MODELSCOPE_SDK_TOKEN": "your_token_here" } } } } ``` ### Option 2: Direct from GitHub ```jsonc { "mcpServers…
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