macOS OCR MCP
Provides OCR (Optical Character Recognition) capabilities using macOS's built-in Vision framework, allowing extraction of text from images with confidence scores and bounding boxes.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@macOS OCR MCPExtract text from ~/Desktop/screenshot.png"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
macOS OCR MCP Tool
This project provides a MetaCall Protocol (MCP) tool to perform Optical Character Recognition (OCR) on images using macOS's built-in Vision framework. It exposes an ocr_image tool that takes an image file path and returns the recognized text along with confidence scores and bounding boxes.
Project Setup
Dependencies
This project relies on Python 3.13+ and the following main dependencies:
ocrmac: For accessing macOS OCR capabilities. See ocrmac.Pillow: For image manipulation.mcp[cli]>=1.7.1: For the MetaCall Protocol server and client.
Installation
It is recommended to use a virtual environment.
Create and activate a virtual environment:
python -m venv .venv source .venv/bin/activateInstall dependencies using
uv:uv sync
Related MCP server: macOS Native OCR MCP Server
Running the MCP Server
To start the MCP server, run main.py:
uv run main.pyThis will start the MCP server, making the ocr_image tool available.
Available MCP Tools
ocr_image
Description: Conducts OCR on the provided image file using macOS's built-in capabilities. Returns recognized text segments, their confidence scores, and bounding box coordinates.
Input:
file_path: str- The absolute or relative path to the image file.Output (Example Success):
{ "filename": "path/to/your/image.png", "annotations": [ { "text": "Hello World", "confidence": 0.95, "bounding_box": [0.1, 0.1, 0.5, 0.05] }, // ... more annotations ] }Output (Example Error):
{ "error": "OCR functionality is only available on macOS." }or
{ "error": "File not found: path/to/nonexistent/image.png" }
Note: This tool will only function correctly on a macOS system due to its reliance on the Vision framework.
Testing with MCP Inspector
You can use the MCP Inspector to connect to the running MCP server and test the tool.
Cursor MCP Configuration
To configure this MCP server in Cursor, you can add the following to your MCP JSON configuration file (e.g., ~/.cursor/mcp.json or project-specific .cursor/mcp.json):
{
"mcpServers": {
"ocrmac": {
"command": "uv",
"args": [
"--directory",
"/path/to/macos-ocr-mcp",
"run",
"main.py"
]
}
}
}This configuration tells Cursor how to start your MCP server. You can then call the ocrmac.ocr_image tool from within Cursor.
This server cannot be deployed
Maintenance
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Verified OCR with per-value coordinates, plus a workspace agents can file documents into and query.
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