ddddocr Smithery MCP Server

A Model Context Protocol (MCP) server for ddddocr that can be deployed on Smithery, providing OCR and CAPTCHA recognition capabilities to AI agents.

Features

• OCR Recognition: Extract text from images with high accuracy

• Text Detection: Identify and locate text regions in images

• Slide CAPTCHA Solving: Match sliding puzzle pieces and find positions

• Color Filtering: Process images with specific color filters

• Probability Output: Get confidence scores for OCR results

Related MCP server: Crawl4AI MCP Server

Quick Start

Deploy on Smithery

1. Fork this repository to your GitHub account

2. Visit Smithery and connect your GitHub account

3. Deploy from your forked repository

4. Use the provided Smithery URL in your Claude Desktop configuration

Local Development

# Install dependencies
npm install

# Build the project
npm run build

# Run in development mode
npm run dev

# Run tests
npm test

Usage

This MCP server provides the following tools:

ocr_recognize

Extract text content from images.

Parameters:

• image (required): Base64 encoded image data

• probability (optional): Return confidence scores

• charset_range (optional): Limit character set (e.g., "0123456789")

• color_filter (optional): Apply color filters

• png_fix (optional): Fix transparent PNG images

text_detection

Detect text regions and bounding boxes in images.

Parameters:

• image (required): Base64 encoded image data

slide_match

Match sliding CAPTCHA pieces to find correct positions.

Parameters:

• target_image (required): Base64 encoded puzzle piece

• background_image (required): Base64 encoded background with gap

• simple_target (optional): Whether target has transparency

slide_comparison

Compare images to find sliding distance for CAPTCHA solving.

Parameters:

• target_image (required): Base64 encoded image with gap

• background_image (required): Base64 encoded complete image

Configuration

Add this server to your Claude Desktop configuration:

{
  "mcpServers": {
    "ddddocr": {
      "command": "npx",
      "args": ["-y", "@smithery/ddddocr-mcp@latest"]
    }
  }
}

Or if deployed on Smithery:

{
  "mcpServers": {
    "ddddocr": {
      "command": "npx",
      "args": ["-y", "@smithery/cli", "run", "your-deployment-url"]
    }
  }
}

Architecture

This server acts as a bridge between MCP clients and the ddddocr service:

1. MCP Layer: Handles protocol communication with AI agents

2. Service Layer: Manages ddddocr process lifecycle

3. API Layer: Communicates with ddddocr HTTP endpoints

4. Processing Layer: Handles image processing and result formatting

Requirements

• Node.js 18+

• ddddocr executable (automatically downloaded in Docker)

• Sufficient memory for image processing (recommend 512MB+)

Security

• Uses non-root user in Docker container

• Validates all input parameters

• Implements proper error handling

• No persistent storage of user images

License

MIT - See LICENSE file for details

Contributing

1. Fork the repository

2. Create a feature branch

3. Make your changes

4. Add tests if applicable

5. Submit a pull request

Support

For issues and questions:

• Check the GitHub Issues

• Review ddddocr documentation

• Visit Smithery Documentation