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DiffuGen - Advanced Local Image Generator with MCP Integration

@CLOUDWERX-DEV

代码仓库主页

基本信息

分类

媒体与设计

许可证

MIT

传输方式

stdio

作者

CLOUDWERX-DEV

关于 DiffuGen - Advanced Local Image Generator with MCP Integration

DiffuGen is a powerful yet user-friendly interface for local\edge image generation. Built on the Model Control Protocol (MCP), it provides a seamless way to interact with various Stable Diffusion models including Flux, SDXL, SD3, and SD1.5. Diffugen also features an OpenAPI Serve

#flux#image#ai#server#code#mcp#stable#generation#cursor#roo#diffusion#cline#schnell#sd#windsurf#generative-ai#comfyui#mcpserver

DiffuGen - Advanced Local Image Generator with MCP Integration 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "DiffuGen": {
      "command": "python3",
      "args": [
        "-m",
        "venv",
        "diffugen_env"
      ]
    }
  }
}

DiffuGen - Advanced Local Image Generator with MCP Integration 工具

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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 DiffuGen?

DiffuGen is an MCP-based image generation server that brings Flux and Stable Diffusion models directly into development environments such as Cursor, Windsurf, Roo Code, and Cline. Built on the optimized stable-diffusion.cpp library, it enables local AI image generation with high performance on modest hardware.

How to use DiffuGen?

After cloning the repository, run the interactive setup script (./setup_diffugen.sh) to install dependencies, build stable-diffusion.cpp, and download models. Configure your IDE’s MCP settings using the provided diffugen.json template. Once connected, ask the LLM to generate images with natural language; the server exposes two tools: generate_stable_diffusion_image and generate_flux_image.

Key features of DiffuGen

  • Supports Flux Schnell, Flux Dev, SDXL, SD3, and SD1.5 models
  • Integrates with MCP-compatible IDEs (Cursor, Windsurf, etc.)
  • OpenAPI REST server for direct HTTP access
  • Cross-platform on Linux, macOS, and Windows (native or WSL)
  • Fine-tune dimensions, steps, CFG scale, seed, and negative prompts
  • CUDA acceleration for faster generation
  • Natural language command interface
  • Smart error recovery and resource tracking

Use cases of DiffuGen

  • Generate visual concepts directly from code comments or chat prompts
  • Quickly iterate on image ideas without leaving the development environment
  • Create custom assets for UI mockups, game sprites, or illustrations
  • Batch generate image variations for design exploration or A/B testing

常见问题

1

What are the minimum system requirements?

CPU: 4-core processor, 8GB RAM, 5GB storage, Python 3.8+. Recommended: 8+ core CPU, 16GB RAM, NVIDIA GPU with 6GB+ VRAM.

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