🪄 ImageSorcery MCP

ComputerVision-based 🪄 sorcery of local image recognition and editing tools for AI assistants

Official website: imagesorcery.net

✅ With ImageSorcery MCP

🪄 ImageSorcery empowers AI assistants with powerful image processing capabilities:

• ✅ Crop, resize, and rotate images with precision
• ✅ Remove background
• ✅ Draw text and shapes on images
• ✅ Add logos and watermarks
• ✅ Detect objects using state-of-the-art models
• ✅ Extract text from images with OCR
• ✅ Use a wide range of pre-trained models for object detection, OCR, and more
• ✅ Do all of this locally, without sending your images to any servers

Just ask your AI to help with image tasks:

"copy photos with pets from folder photos to folder pets"

"Find a cat at the photo.jpg and crop the image in a half in height and width to make the cat be centered"

😉 _Hint: Use full path to your files"._

"Enumerate form fields on this form.jpg with foduucom/web-form-ui-field-detection model and fill the form.md with a list of described fields"

😉 _Hint: Specify the model and the confidence"._

😉 _Hint: Add "use imagesorcery" to make sure it will use the proper tool"._

Your tool will combine multiple tools listed below to achieve your goal.

🛠️ Available Tools

😉 _Hint: detailed information and usage instructions for each tool can be found in the tool's /src/imagesorcery_mcp/tools/README.md._

📚 Available Resources

😉 _Hint: detailed information and usage instructions for each resource can be found in the resource's /src/imagesorcery_mcp/resources/README.md._

💬 Available Prompts

😉 _Hint: detailed information and usage instructions for each prompt can be found in the prompt's /src/imagesorcery_mcp/prompts/README.md._

🚀 Getting Started

Requirements

• Python 3.10 or higher
• pipx (recommended) - for easy installation and virtual environment management
• ffmpeg, libsm6, libxext6, libgl1-mesa-glx - system libraries required by OpenCV
• Claude.app, Cline, or another MCP client

These dependencies are typically included with OpenCV installation and don't require separate installation. But they might be missing in some virtual environments like Docker.

For Ubuntu/Debian systems:

sudo apt-get update && sudo apt-get install -y ffmpeg libsm6 libxext6 libgl1-mesa-glx

For Docker containers: Add this line to your Dockerfile:

RUN apt-get update && apt-get install -y ffmpeg libsm6 libxext6 libgl1-mesa-glx

Installation

1.  Load MCP documentation if you have the tool for it. It will give you path to *MCP-configuration file* and other needed instructions.
2.  Run command `pipx install imagesorcery-mcp`
3.  Run command `imagesorcery-mcp --post-install`
4.  Create or modify *MCP-configuration file*.
5.  Add the `imagesorcery-mcp` server configuration to the `mcpServers` object in the *MCP-configuration file*
    `"imagesorcery-mcp": {"command": "imagesorcery-mcp","timeout": 100}`
6.  Prompt the user for permission and enable telemetry by calling `config(action="set", key="telemetry.enabled", value=True, persist=True)`.
7.  Attempt completion, indicating that the installation and configuration are complete.

#### Method 1: Using pipx (Recommended)

pipx is the recommended way to install ImageSorcery MCP as it automatically handles virtual environment creation and management, making the installation process much simpler.

1. Install pipx (if not already installed):

    # On macOS with Homebrew:
    brew install pipx

    # On Ubuntu/Debian:
    sudo apt update && sudo apt install pipx

    # On other systems with pip:
    pip install --user pipx
    pipx ensurepath

1. Install ImageSorcery MCP with pipx:

    pipx install imagesorcery-mcp

1. Run the post-installation script:

This step is crucial. It downloads the required models and attempts to install the clip Python package from GitHub.

    imagesorcery-mcp --post-install

#### Method 2: Manual Virtual Environment (Plan B)

For reliable installation of all components, especially the clip package (installed via the post-install script), it is strongly recommended to use Python's built-in venv module instead of uv venv.

1. Create and activate a virtual environment:

    python -m venv imagesorcery-mcp
    source imagesorcery-mcp/bin/activate  # For Linux/macOS
    # source imagesorcery-mcp\Scripts\activate    # For Windows

1. Install the package into the activated virtual environment: