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image-gen-mcp

MCP.Pizza Chef: Ichigo3766

image-gen-mcp is an MCP server that enables text-to-image generation by interfacing with the Stable Diffusion WebUI API, including ForgeUI and AUTOMATIC-1111. It requires a running Stable Diffusion WebUI instance with API access enabled and provides seamless integration for generating images from textual prompts within MCP-enabled environments.

Use This MCP server To

Generate images from text prompts using Stable Diffusion API Integrate AI image generation into MCP workflows Automate creative image creation in development pipelines Enable real-time image generation in chat or IDE environments Create visual content for marketing or design projects Prototype visual concepts from natural language descriptions

README

image-gen MCP Server

A MCP server that provides text-to-image generation capabilities using Stable Diffusion WebUI API (ForgeUI/AUTOMATIC-1111).

Image Generation Server MCP server

Installation

Prerequisites

  • Node.js
  • Access to a Stable Diffusion WebUI instance with API enabled
  • The WebUI must have --api flag enabled when starting

Setup

  1. Clone the repository:
git clone https://github.com/Ichigo3766/image-gen-mcp.git
cd image-gen-mcp
  1. Install dependencies:
npm install
  1. Build the server:
npm run build
  1. Add the server configuration to your environment:
{
  "mcpServers": {
    "image-gen": {
      "command": "node",
      "args": [
        "/path/to/image-gen-mcp/build/index.js"
      ],
      "env": {
        "SD_WEBUI_URL": "http://your-sd-webui-url:7860",
        "SD_AUTH_USER": "your-username",  // Optional: if authentication is enabled
        "SD_AUTH_PASS": "your-password",  // Optional: if authentication is enabled
        "SD_OUTPUT_DIR": "/path/to/output/directory",
        "SD_RESIZE_MODE": "0",           // Optional: upscaling mode (0=multiplier, 1=dimensions)
        "SD_UPSCALE_MULTIPLIER": "4",    // Optional: default upscale multiplier
        "SD_UPSCALE_WIDTH": "512",       // Optional: default upscale width
        "SD_UPSCALE_HEIGHT": "512",      // Optional: default upscale height
        "SD_UPSCALER_1": "R-ESRGAN 4x+", // Optional: default primary upscaler
        "SD_UPSCALER_2": "None"          // Optional: default secondary upscaler
      }
    }
  }
}

Replace the environment variables with your values:

  • SD_WEBUI_URL: URL of your Stable Diffusion WebUI instance
  • SD_AUTH_USER: Username for basic auth (if enabled)
  • SD_AUTH_PASS: Password for basic auth (if enabled)
  • SD_OUTPUT_DIR: Directory where generated images will be saved
  • SD_RESIZE_MODE: Default upscaling mode (0 for multiplier, 1 for dimensions)
  • SD_UPSCALE_MULTIPLIER: Default upscale multiplier when resize_mode is 0
  • SD_UPSCALE_WIDTH: Default target width when resize_mode is 1
  • SD_UPSCALE_HEIGHT: Default target height when resize_mode is 1
  • SD_UPSCALER_1: Default primary upscaler model
  • SD_UPSCALER_2: Default secondary upscaler model

Features

Tools

  • generate_image - Generate images using Stable Diffusion

    • Parameters:
      • prompt (required): Text description of the desired image
      • negative_prompt: Things to exclude from the image
      • steps: Number of sampling steps (default: 4, range: 1-150)
      • width: Image width (default: 1024, range: 512-2048)
      • height: Image height (default: 1024, range: 512-2048)
      • cfg_scale: CFG scale (default: 1, range: 1-30)
      • sampler_name: Sampling algorithm (default: "Euler")
      • scheduler_name: Scheduler algorithm (default: "Simple")
      • seed: Random seed (-1 for random)
      • batch_size: Number of images to generate (default: 1, max: 4)
      • restore_faces: Enable face restoration
      • tiling: Generate tileable images
      • output_path: Custom output path for the generated image
  • get_sd_models - Get list of available Stable Diffusion models

    • No parameters required
    • Returns an array of model names
  • set_sd_model - Set the active Stable Diffusion model

    • Parameters:
      • model_name (required): Name of the model to set as active
  • get_sd_upscalers - Get list of available upscaler models

    • No parameters required
    • Returns an array of upscaler names
  • upscale_images - Upscale one or more images using Stable Diffusion

    • Parameters:
      • images (required): Array of image file paths to upscale
      • resize_mode: 0 for multiplier mode, 1 for dimension mode (default: from env)
      • upscaling_resize: Upscale multiplier when resize_mode=0 (default: from env)
      • upscaling_resize_w: Target width in pixels when resize_mode=1 (default: from env)
      • upscaling_resize_h: Target height in pixels when resize_mode=1 (default: from env)
      • upscaler_1: Primary upscaler model (default: from env)
      • upscaler_2: Secondary upscaler model (default: from env)
      • output_path: Custom output directory for upscaled images

Development

For development with auto-rebuild:

npm run watch

Error Handling

Common issues and solutions:

  1. Make sure your Stable Diffusion WebUI is running with the --api flag
  2. Check if the WebUI URL is accessible from where you're running the MCP server
  3. If using authentication, ensure credentials are correct
  4. Verify the output directory exists and has write permissions
  5. When upscaling, ensure the input image files exist and are readable

License

This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.

image-gen-mcp FAQ

How do I set up the image-gen-mcp server?
Clone the repo, install dependencies with npm, build the server, and configure it to connect to a Stable Diffusion WebUI instance with API enabled.
What prerequisites are needed to run image-gen-mcp?
You need Node.js and access to a Stable Diffusion WebUI instance running with the --api flag enabled.
Can image-gen-mcp work with different Stable Diffusion WebUI variants?
Yes, it supports ForgeUI and AUTOMATIC-1111 variants of the Stable Diffusion WebUI API.
Is it possible to customize the image generation parameters?
Yes, you can configure parameters through the API calls to tailor image outputs.
How does image-gen-mcp integrate with other MCP components?
It acts as a server exposing image generation capabilities that MCP clients can call to embed images in workflows.
What LLM providers can I use with image-gen-mcp?
While image-gen-mcp focuses on image generation, it can be combined with LLMs like OpenAI, Claude, and Gemini for multimodal workflows.
Is the image generation process synchronous or asynchronous?
The server handles requests asynchronously, allowing efficient processing of multiple image generation tasks.
Can I run image-gen-mcp on any platform?
It requires Node.js and network access to a Stable Diffusion WebUI instance, so it can run on most platforms supporting these.