mcp-ocr-server

dangvinh/mcp-ocr-server

3.2

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MCP OCR Server is a high-performance OCR solution using native Tesseract (C++) and Node.js, designed for integration with ChatGPT Desktop and other MCP clients.

MCP OCR Server

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MCP server for OCR using native Tesseract (C++), built with Node.js, delivering high-performance OCR and integrable with ChatGPT Desktop.

🚧 Work in Progress 🚧

✨ Features (planned)

  • High-performance OCR via native Tesseract (C++)
  • Node.js MCP server wrapper for easy integration
  • Compatible with ChatGPT Desktop and other MCP clients
  • Benchmark vs tesseract.js

📌 Roadmap

  • Step 1: C++ OCR CLI tool
  • Step 2: Node.js MCP server wrapper
  • Step 3: ChatGPT Desktop configuration guide
  • Step 4: Benchmark results
  • Step 5: Demo video

🔧 Tech Stack

  • C++ (Tesseract OCR)
  • Node.js + TypeScript (@modelcontextprotocol/sdk)
  • JSON-RPC 2.0 (MCP standard)

🛠 Installation

1. Install Tesseract OCR

macOS
brew install tesseract
# Optional: install additional languages
brew install tesseract-lang
Linux (Ubuntu/Debian)
sudo apt update
sudo apt install tesseract-ocr libtesseract-dev libleptonica-dev
# Optional: install Vietnamese language
sudo apt install tesseract-ocr-vie
Windows
choco install tesseract
  • Add the installation path to your PATH environment variable.

2. Clone the repository

git clone https://github.com/dangvinh/mcp-ocr-server.git
cd mcp-ocr-server/cpp

3. Build the project with CMake

You can build the C++ OCR engine using the provided npm script. Run:

npm run build-core

This command will create the cpp/build-core directory, configure the project with CMake, and build the static library and CLI tool.

What it builds:
  • libmcp_ocr.a static library
  • ocr_cli executable in cpp/build-core/bin (or equivalent)
Running tests
# From the build directory
ctest --verbose
  • This will run all GoogleTest-based tests.
  • Ensure test images or resources exist in cpp/tests or examples/.
  • The setup works cross-platform (macOS, Linux, Windows).

4. Build the Node.js addon

The Node.js addon can be built using the provided npm script. Run:

npm run build-addon

This command runs node-gyp inside the cpp/ directory and produces the compiled addon (ocr_addon.node) inside cpp/build/Release/. This addon is required for Node.js integration with the C++ core.

🗂 Setup tessdata

The OCR engine requires trained data files to work. Please follow these steps:

  1. Create a tessdata folder in the project root:
mkdir tessdata
  1. Download the English trained data:
wget https://github.com/tesseract-ocr/tessdata/raw/main/eng.traineddata -P tessdata/

  1. For other languages, download the corresponding .traineddata files into tessdata/.

  2. Ensure your .env or .env.example has:

TESSDATA_PREFIX=./tessdata
OCR_LANG=eng

4. Run OCR CLI

./ocr_cli path/to/image.png

Ensure the tessdata folder is accessible for language files. The project supports macOS, Linux, and Windows (cross-platform).