🪄 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

| Tool | Description | Example Prompt | |------|-------------|----------------| | blur | Blurs specified rectangular or polygonal areas of an image using OpenCV. Can also invert the provided areas e.g. to blur background. | "Blur the area from (150, 100) to (250, 200) with a blur strength of 21 in my image 'test_image.png' and save it as 'output.png'" | | change_color | Changes the color palette of an image | "Convert my image 'test_image.png' to sepia and save it as 'output.png'" | | config | View and update ImageSorcery MCP configuration settings | "Show me the current configuration" or "Set the default detection confidence to 0.8" | | crop | Crops an image using OpenCV's NumPy slicing approach | "Crop my image 'input.png' from coordinates (10,10) to (200,200) and save it as 'cropped.png'" | | detect | Detects objects in an image using models from Ultralytics. Can return segmentation masks (as PNG files) or polygons. | "Detect objects in my image 'photo.jpg' with a confidence threshold of 0.4" | | draw_arrows | Draws arrows on an image using OpenCV | "Draw a red arrow from (50,50) to (150,100) on my image 'photo.jpg'" | | draw_circles | Draws circles on an image using OpenCV | "Draw a red circle with center (100,100) and radius 50 on my image 'photo.jpg'" | | draw_lines | Draws lines on an image using OpenCV | "Draw a red line from (50,50) to (150,100) on my image 'photo.jpg'" | | draw_rectangles | Draws rectangles on an image using OpenCV | "Draw a red rectangle from (50,50) to (150,100) and a filled blue rectangle from (200,150) to (300,250) on my image 'photo.jpg'" | | draw_texts | Draws text on an image using OpenCV | "Add text 'Hello World' at position (50,50) and 'Copyright 2023' at the bottom right corner of my image 'photo.jpg'" | | fill | Fills specified rectangular, polygonal, or mask-based areas of an image with a color and opacity, or makes them transparent. Can also invert the provided areas e.g. to remove background. | "Fill the area from (150, 100) to (250, 200) with semi-transparent red in my image 'test_image.png'" | | find | Finds objects in an image based on a text description. Can return segmentation masks (as PNG files) or polygons. | "Find all dogs in my image 'photo.jpg' with a confidence threshold of 0.4" | | get_metainfo | Gets metadata information about an image file | "Get metadata information about my image 'photo.jpg'" | | ocr | Performs Optical Character Recognition (OCR) on an image using EasyOCR | "Extract text from my image 'document.jpg' using OCR with English language" | | overlay | Overlays one image on top of another, handling transparency | "Overlay 'logo.png' on top of 'background.jpg' at position (10, 10)" | | resize | Resizes an image using OpenCV | "Resize my image 'photo.jpg' to 800x600 pixels and save it as 'resized_photo.jpg'" | | rotate | Rotates an image using imutils.rotate_bound function | "Rotate my image 'photo.jpg' by 45 degrees and save it as 'rotated_photo.jpg'" |

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

📚 Available Resources

| Resource URI | Description | Example Prompt | |--------------|-------------|----------------| | models://list | Lists all available models in the models directory | "Which models are available in ImageSorcery?" |

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

💬 Available Prompts

| Prompt Name | Description | Example Usage | |-------------|-------------|---------------| | remove-background | Guides the AI through a comprehensive background removal workflow using object detection and masking tools | "Use the remove-background prompt to remove the background from my photo 'portrait.jpg', keeping only the person" |

😉 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.

0. 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
   

2. 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
   

2. Install the package into the activated virtual environment: You can use pip or uv pip.

   pip install imagesorcery-mcp
   # OR, if you prefer using uv for installation into the venv:
   # uv pip install imagesorcery-mcp
   

3. Run the post-installation script: This step is crucial. It downloads the required models