mcp-ocr

mcp-ocr

3
ai_chatbot

The MCP OCR Server is a robust, production-grade OCR solution built using the Model Context Protocol. Designed for simplicity and efficiency, it extracts text from various image sources, supports multiple languages, and provides robust error handling.

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

  1. Start the server:
python -m mcp_ocr
  1. 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

  1. Clone the repository:
git clone https://github.com/rjn32s/mcp-ocr.git
cd mcp-ocr
  1. Set up development environment:
uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
uv pip install -e .
  1. Run tests:
pytest

Contributing

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. 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 file for details.

Acknowledgments