by sunriseapps
Unlock powerful image manipulation with ImageSorcery: resize, crop, detect objects, and perform optical character recogn
Provides local image processing and computer vision capabilities including editing, object detection, and OCR text extraction. Works entirely offline without sending images to external servers.
ImageSorcery is a community-built MCP server published by sunriseapps that provides AI assistants with tools and capabilities via the Model Context Protocol. Unlock powerful image manipulation with ImageSorcery: resize, crop, detect objects, and perform optical character recogn It is categorized under ai ml.
You can install ImageSorcery in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
ImageSorcery is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
ImageSorcery has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
According to our notes, ImageSorcery benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Strong directory entry: ImageSorcery surfaces stars and publisher context so we could sanity-check maintenance before adopting.
ImageSorcery is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
ImageSorcery is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
We evaluated ImageSorcery against two servers with overlapping tools; this profile had the clearer scope statement.
Strong directory entry: ImageSorcery surfaces stars and publisher context so we could sanity-check maintenance before adopting.
ImageSorcery has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
We wired ImageSorcery into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
I recommend ImageSorcery for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
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ComputerVision-based 🪄 sorcery of local image recognition and editing tools for AI assistants
Official website: imagesorcery.net
🪄 ImageSorcery empowers AI assistants with powerful image processing capabilities:
Just ask your AI to help with image tasks:
"copy photos with pets from folder
photosto folderpets"
"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.jpgwithfoduucom/web-form-ui-field-detectionmodel and fill theform.mdwith 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.
| 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.
| 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.
| 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.
Python 3.10 or higherpipx (recommended) - for easy installation and virtual environment managementffmpeg, libsm6, libxext6, libgl1-mesa-glx - system libraries required by OpenCVClaude.app, Cline, or another MCP clientThese 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
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.
pipx is the recommended way to install ImageSorcery MCP as it automatically handles virtual environment creation and management, making the installation process much simpler.
# 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
Install ImageSorcery MCP with pipx:
pipx install imagesorcery-mcp
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
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.
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
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
Run the post-installation script: This step is crucial. It downloads the required models
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.