ImageSorcery MCP

ImageSorcery MCP

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

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Overview

ImageSorcery MCP is a self-contained, computer-vision-based MCP server that empowers AI assistants with a rich, locally-running image processing toolkit. It exposes tools for cropping, resizing, rotating images, removing backgrounds, drawing text and shapes, and applying logos or watermarks. It includes object detection using state-of-the-art models and Optical Character Recognition (OCR) to extract text from images. The server supports a broad range of pre-trained models for object detection and OCR, and can operate entirely offline, ensuring user data stays on the device. The system consists of a configurable MCP server with a set of tools, prompts, and resources, and can run in multiple transport modes (STDIO, streamable HTTP, SSE). It provides post-install scripts to download models (e.g., YOLO models, CLIP), creates a config.toml, and sets up a models directory and model descriptions. It can be integrated with MCP clients (Claude, Cursor, Cline) and configured via mcpServers, with autoApprove lists of available tools and a configurable timeout. The README also describes privacy/telemetry, installation, and how to run the server locally.

Details

Owner
sunriseapps
Language
Python
License
MIT License
Updated
2025-12-07

Features

Local image processing toolkit

Crop, resize, and rotate images with precision using OpenCV, all locally via MCP.

Background removal

Remove or replace backgrounds using masking and advanced image editing.

Annotation and drawing

Draw texts and shapes on images to annotate results.

Watermarks and logos

Add logos and watermarks to protect branding and ownership.

Object detection with pre-trained models

Detect objects using Ultralytics models and other pre-trained detectors.

OCR text extraction

Extract text from images using Optical Character Recognition (OCR).

Offline/local operation

All processing happens locally without sending data to external servers.

Model management and post-install

Post-install scripts download models, manage descriptions, and install CLIP for text tasks.

Audience

AI developersIntegrate ImageSorcery MCP into AI assistants to perform local image processing tasks (crop, detect, OCR) via MCP.
MCP clientsConnect with MCP clients like Claude, Cursor, or Cline to execute image tasks locally.
ResearchersExperiment with image processing workflows using pre-trained models and local inference without cloud data.

Tags

image processingcomputer visionlocal processingobject detectionOCRmodel managementofflineMCP