ymeng98/ddddocr-smithery-mcp
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A Model Context Protocol (MCP) server for ddddocr that can be deployed on Smithery, providing OCR and CAPTCHA recognition capabilities to AI agents.
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
Quick Start
Deploy on Smithery
- Fork this repository to your GitHub account
- Visit Smithery and connect your GitHub account
- Deploy from your forked repository
- 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 dataprobability
(optional): Return confidence scorescharset_range
(optional): Limit character set (e.g., "0123456789")color_filter
(optional): Apply color filterspng_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 piecebackground_image
(required): Base64 encoded background with gapsimple_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 gapbackground_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:
- MCP Layer: Handles protocol communication with AI agents
- Service Layer: Manages ddddocr process lifecycle
- API Layer: Communicates with ddddocr HTTP endpoints
- 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
- Fork the repository
- Create a feature branch
- Make your changes
- Add tests if applicable
- Submit a pull request
Support
For issues and questions:
- Check the GitHub Issues
- Review ddddocr documentation
- Visit Smithery Documentation