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GIMP-MCP

libreearth/gimp-mcp
106
Summary

This runs a local server that bridges GIMP's Python API to Claude or other MCP clients for AI-assisted image editing. You get programmatic access to GIMP operations like creating layers, loading files, filling selections, and setting layer offsets, plus AI-specific workflows for background removal and inpainting. Instead of manually scripting GIMP edits or context-switching between your editor and the UI, you describe what you want and let the AI manipulate layers and selections directly. Works with GIMP 2.10 or later by dropping a Python plugin into your plugins directory and running the MCP server locally. Best when you need to automate repetitive edits or prototype complex compositions where natural language is faster than clicking through menus.

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GIMP-MCP: Integrating GIMP with AI through Model Context Protocol

GIMP-MCP is an initiative to integrate the Model Context Protocol (MCP) into the GNU Image Manipulation Program (GIMP), enabling seamless interaction between GIMP and AI models. This integration allows users to harness advanced AI capabilities directly within GIMP, enhancing image editing workflows with intelligent automation and context-aware operations.

Table of Contents

  • Introduction
  • Features
  • Installation
    • Prerequisites
    • Setting Up the MCP Server
    • Integrating MCP with GIMP
  • Usage Examples
    • AI-Powered Background Removal
    • Image Inpainting with AI
  • Human-AI Interaction Prompts
  • Available API Commands
  • Contributing
  • License
  • Acknowledgments

Introduction

The Model Context Protocol (MCP) is an open standard developed to facilitate seamless integration between AI systems and external applications. By implementing MCP within GIMP, users can leverage AI models for tasks such as object recognition, style transfer, and automated enhancements, thereby extending GIMP's native functionalities.

Features

  • AI Integration: Connect GIMP with state-of-the-art AI models for enhanced image processing capabilities.
  • Automated Workflows: Utilize AI to perform repetitive tasks, allowing for more efficient editing processes.
  • Context-Aware Operations: AI models can interpret and manipulate images based on contextual understanding, leading to more intelligent edits.

Installation

Prerequisites

Before integrating MCP with GIMP, ensure you have the following:

  • GIMP 2.10 or later installed on your system.
  • Python 3.x installed.
  • Basic knowledge of Python scripting and GIMP's plugin architecture.

Setting Up the MCP Server

  1. Clone the MCP Repository:
    git clone https://github.com/modelcontextprotocol/servers.git
    cd servers
    
     2.	Install Dependencies:
    

Ensure you have the necessary Python libraries:

pip install -r requirements.txt

3.	Run the MCP Server:

Start the server to enable communication between GIMP and AI models:

python mcp_server.py

Integrating MCP with GIMP 1. Locate GIMP’s Plugin Directory: • Linux: ~/.config/GIMP/2.10/plug-ins/ • Windows: C:\Users<username>\AppData\Roaming\GIMP\2.10\plug-ins
• macOS: ~/Library/Application Support/GIMP/2.10/plug-ins/ 2. Copy the Plugin File: Place the gimp_mcp_plugin.py file into GIMP’s plugin directory. 3. Make the Plugin Executable (Linux/macOS):

chmod +x ~/.config/GIMP/2.10/plug-ins/gimp_mcp_plugin.py

4.	Restart GIMP:

Relaunch GIMP to recognize the new plugin. You should see the MCP integration under Filters > AI Tools.

Usage Examples

AI-Powered Background Removal

Leverage AI to automatically remove backgrounds from images: 1. Open an Image: • Load your desired image into GIMP. 2. Initiate Background Removal: • Navigate to Filters > AI Tools > Remove Background. • The AI model will process the image and remove the background intelligently.

Image Inpainting with AI

Fill missing or corrupted parts of an image using AI-based inpainting: 1. Select the Area to Inpaint: • Use GIMP’s selection tools to highlight the area needing inpainting. 2. Apply AI Inpainting: • Go to Filters > AI Tools > Inpaint Selection. • The AI model will reconstruct the selected area based on surrounding content.

Human-AI Interaction Prompts

To effectively utilize AI within GIMP via MCP, consider the following interaction prompts: • Object Recognition: • Prompt: “Identify and select all objects in the image.” • AI Response: The AI highlights and categorizes each object detected. • Style Transfer: • Prompt: “Apply Van Gogh’s Starry Night style to the current image.” • AI Response: The image is transformed to emulate the specified artistic style. • Image Enhancement: • Prompt: “Enhance the image resolution and reduce noise.” • AI Response: The AI upscales the image and applies noise reduction techniques.

Available API Commands

The following are some of the API commands available through the MCP integration: • gimp_image_new: Create a new image. • gimp_layer_new: Add a new layer to an image. • gimp_text_layer_new: Create a new text layer. • gimp_file_load: Load an image file. • gimp_file_save: Save the current image to a file. • gimp_edit_fill: Fill a selection or layer with a specified color. • gimp_context_set_foreground: Set the foreground color. • gimp_layer_set_offsets: Set the position of a layer within an image.

For a comprehensive list of commands and their parameters, refer to the GIMP Python API documentation.

Contributing

We welcome contributions to enhance GIMP-MCP: 1. Fork the Repository: • Click the “Fork” button on GitHub. 2. Create a Feature Branch:

git checkout -b feature/your-feature-name

3.	Commit Your Changes:

git commit -m "Add feature: your feature description"

4.	Push to Your Fork:

git push origin feature/your-feature-name

5.	Submit a Pull Request:
•	Describe your changes and submit for review.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgments

We extend our gratitude to the developers and researchers who have contributed to integrating AI capabilities within GIMP, making advanced image editing accessible to all.

⸻

Note: The integration of MCP with GIMP is an ongoing project. For the latest updates and community support, visit our discussion forum.

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UpdatedDec 15, 2025
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