Mcp Ocr
Description
# MCP OCR Server [](https://pypi.org/project/mcp-ocr/) [](https://pepy.te…
About
# MCP OCR Server [](https://pypi.org/project/mcp-ocr/) [](https://pepy.tech/project/mcp-ocr) A production-grade…
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- Author
- rjn32s
- GitHub stars
- 38
- Downloads
- 681
- Categories
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- Extracts text from images using Tesseract OCR
- Supports local files, image URLs, and raw bytes
- Automatic Tesseract installation on macOS, Linux, and Windows
- Multi-language OCR support
- Production-ready error handling
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Mcp OcrCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Install with pip install mcp-ocr or uv pip install mcp-ocr, then start the server with python -m mcp_ocr. To use with Claude for Desktop, add an entry named "ocr" in the mcpServers section of the configuration file, specifying the same command. The server exposes two tools: perform_ocr (for extracting text from files, URLs, or raw bytes) and get_supported_languages (to list available OCR languages).
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"mcp ocr": {
"mcp-ocr": {
"command": "uv",
"args": [
"pip",
"install",
"mcp-ocr"
]
}
}
}
}McpServers
{
"mcp-ocr": {
"command": "uv",
"args": [
"pip",
"install",
"mcp-ocr"
]
}
}A production-grade OCR server built using MCP (Model Context Protocol) that provides OCR capabilities through a simple interface.
- Extract text from images using Tesseract OCR
- Support for multiple input types:
- Local image files
- Image URLs
- Raw image bytes
# 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)
- Configure Claude for Desktop: Add to~/Library/Application Support/Claude/claude_desktop_config.json:
{ "mcpServers": { "ocr": { "command": "python", "args": ["-m", "mcp_ocr"] } } }
# From file perform_ocr("/path/to/image.jpg") # From URL perform_ocr("https://example.com/image.jpg") # From bytes perform_ocr(image_bytes)
git clone https://github.com/rjn32s/mcp-ocr.git cd mcp-ocr
uv venv source .venv/bin/activate # On Windows: .venv\Scripts\activate uv pip install -e .
- 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
- Never commit API tokens or sensitive credentials
- Use environment variables or secure credential storage
- Follow GitHub's security best practices
This project is licensed under the MIT License - see theLICENSEfile for details.
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