What are the prerequisites for installing GIMP-MCP?
GIMP 2.10 or later, Python 3.x, and basic knowledge of Python scripting and GIMP’s plugin architecture are required.
@libreearth
基本情報
Gimp MCP Server
ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
GIMP-MCP integrates the Model Context Protocol (MCP) into the GNU Image Manipulation Program (GIMP), enabling seamless interaction between GIMP and AI models. It is designed for users who want to harness advanced AI capabilities directly within GIMP for intelligent image editing and automation.
Install prerequisites (GIMP 2.10+, Python 3.x), clone the MCP servers repository, install dependencies (pip install -r requirements.txt), and run the MCP server (python mcp_server.py). Place the gimp_mcp_plugin.py file into GIMP’s plugin directory, make it executable (Linux/macOS), and restart GIMP. Access AI tools under Filters > AI Tools (e.g., Remove Background, Inpaint Selection). Use human‑AI prompts like “Identify and select all objects” or “Apply Van Gogh’s Starry Night style.”
gimp_image_new, gimp_file_save).GIMP 2.10 or later, Python 3.x, and basic knowledge of Python scripting and GIMP’s plugin architecture are required.
Copy `gimp_mcp_plugin.py` into GIMP’s plugin directory: `~/.config/GIMP/2.10/plug-ins/` (Linux), `C:\Users\<username>\AppData\Roaming\GIMP\2.10\plug-ins\` (Windows), or `~/Library/Application Support/GIMP/2.10/plug-ins/` (macOS). Make it executable on Linux/macOS.
After cloning the MCP servers repository and installing dependencies, run `python mcp_server.py` in the `servers` directory to start the server that enables communication between GIMP and AI models.
The README lists commands like `gimp_image_new`, `gimp_layer_new`, `gimp_text_layer_new`, `gimp_file_load`, `gimp_file_save`, `gimp_edit_fill`, `gimp_context_set_foreground`, and `gimp_layer_set_offsets`. See the GIMP Python API documentation for a full list.
Fork the repository, create a feature branch, commit changes, push to your fork, and submit a pull request. The project is licensed under MIT.

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