MCP OCR Server
An MCP server for Optical Character Recognition (OCR) using the Tesseract engine.
MCP OCR Server
A production-grade OCR server built using MCP (Model Context Protocol) that provides OCR capabilities through a simple interface.
Features
- Extract text from images using Tesseract OCR
- Support for multiple input types:
- Local image files
- Image URLs
- Raw image bytes
- Automatic Tesseract installation
- Support for multiple languages
- Production-ready error handling
Installation
# Using pip
pip install mcp-ocr
# Using uv
uv pip install mcp-ocr
Tesseract will be installed automatically on supported platforms:
- macOS (via Homebrew)
- Linux (via apt, dnf, or pacman)
- Windows (manual installation instructions provided)
Usage
As an MCP Server
- Start the server:
python -m mcp_ocr
- Configure Claude for Desktop:
Add to
~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"ocr": {
"command": "python",
"args": ["-m", "mcp_ocr"]
}
}
}
Available Tools
perform_ocr
Extract text from images:
# From file
perform_ocr("/path/to/image.jpg")
# From URL
perform_ocr("https://example.com/image.jpg")
# From bytes
perform_ocr(image_bytes)
get_supported_languages
List available OCR languages:
get_supported_languages()
Development
- Clone the repository:
git clone https://github.com/rjn32s/mcp-ocr.git
cd mcp-ocr
- Set up development environment:
uv venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
uv pip install -e .
- Run tests:
pytest
Contributing
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
Security
- Never commit API tokens or sensitive credentials
- Use environment variables or secure credential storage
- Follow GitHub's security best practices
License
This project is licensed under the MIT License - see the LICENSE file for details.
Acknowledgments
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