ReadPDFx - OCR PDF MCP Server

ReadPDFx - OCR PDF MCP Server

Provides intelligent OCR and PDF processing capabilities that automatically detect whether PDFs contain digital text or scanned images and apply appropriate extraction methods. Supports text extraction, OCR processing, structure analysis, and batch operations.

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ReadPDFx - OCR PDF MCP Server

Official MCP SDK STDIO Server - MCP Protocol 2025-06-18 Compliant

MCP Protocol Python MCP SDK License

<div align="left" style="display: flex; align-items: center; gap: 20px;"> <img src="./logo.png" alt="Read_PDF Logo" width="100" style="flex-shrink: 0;"> <div> ReadPDFx is a comprehensive MCP (Model Context Protocol) server that provides intelligent OCR and PDF processing capabilities using the official MCP SDK with STDIO transport. It automatically detects whether a PDF contains digital text or scanned images and applies the appropriate processing method. </div> </div>

โšก Quick Start (STDIO Server)

1. Install Dependencies

pip install -r requirements.txt

2. Validate Installation

# Test imports and tools
python validate_tools.py

3. Client Integration

The server runs via STDIO protocol - configure your MCP client:

Claude Desktop:

{
  "mcpServers": {
    "ocr-pdf": {
      "command": "python",
      "args": ["d:/AI/MCP/python/ocr_pdf_mcp/mcp_server_stdio.py"],
      "env": {}
    }
  }
}

๐Ÿš€ Features

  • ๐ŸŽฏ Official MCP SDK: Built with official FastMCP framework
  • ๐Ÿ“ก STDIO Transport: Standard MCP protocol over STDIO
  • ๐Ÿง  Smart PDF Processing: Automatically detects digital vs scanned content
  • ๐Ÿ”ง 5 OCR Tools: Text extraction, OCR processing, combined operations
  • ๐ŸŒ Universal Client Support: Claude Desktop, LM Studio, Continue.dev, Cursor
  • โšก Lightweight: ~200 lines vs 800+ in HTTP implementation
  • ๐Ÿ›ก๏ธ Production Ready: Comprehensive error handling and logging
  • ๐Ÿ“‹ Auto Tool Registration: Decorators handle tool discovery

๐Ÿ”ง Installation

Prerequisites

  • Python 3.8+
  • Tesseract OCR

Windows

# Install Python dependencies
pip install -r requirements.txt

# Install Tesseract
choco install tesseract

macOS

pip install -r requirements.txt
brew install tesseract

Linux

pip install -r requirements.txt
sudo apt-get install tesseract-ocr

๐Ÿ“‹ Available Tools

1. Smart PDF Processing

Intelligent processing with automatic OCR detection:

{
  "name": "process_pdf_smart",
  "arguments": {
    "pdf_path": "/path/to/document.pdf",
    "language": "eng"
  }
}

2. PDF Text Extraction

Direct text extraction from digital PDFs:

{
  "name": "extract_pdf_text", 
  "arguments": {
    "pdf_path": "/path/to/document.pdf",
    "page_range": "1-5"
  }
}

3. OCR Processing

OCR on image files:

{
  "name": "perform_ocr",
  "arguments": {
    "image_path": "/path/to/image.png",
    "language": "eng"
  }
}

4. PDF Structure Analysis

Analyze document structure and metadata:

{
  "name": "analyze_pdf_structure",
  "arguments": {
    "pdf_path": "/path/to/document.pdf"
  }
}

5. Batch Processing

Process multiple files:

{
  "name": "batch_process_pdfs",
  "arguments": {
    "input_directory": "/path/to/pdfs/",
    "output_directory": "/path/to/output/",
    "file_pattern": "*.pdf"
  }
}

๐Ÿ”Œ Client Integration

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "readpdfx": {
      "command": "python",
      "args": ["path/to/readpdfx/run.py"],
      "env": {
        "PYTHONPATH": "path/to/readpdfx"
      }
    }
  }
}

LM Studio

Configure MCP server with:

  • Command: python
  • Args: path/to/readpdfx/run.py
  • URL: http://localhost:8000 (HTTP mode)

Continue.dev

Add to config.json:

{
  "contextProviders": [
    {
      "name": "mcp",
      "params": {
        "command": "python",
        "args": ["path/to/readpdfx/run.py"]
      }
    }
  ]
}

Cursor

Configure in settings.json:

{
  "mcp.servers": {
    "readpdfx": {
      "command": "python",
      "args": ["path/to/readpdfx/run.py"]
    }
  }
}

๐Ÿ“ See client-configs/ for detailed integration guides.

๐ŸŒ API Endpoints

MCP Protocol Endpoints

  • POST /mcp/initialize - Initialize MCP session
  • POST /mcp/tools/list - List available tools
  • POST /mcp/tools/call - Call MCP tools
  • GET /mcp/manifest - Get MCP manifest

HTTP Endpoints

  • GET /health - Health check
  • POST /jsonrpc - JSON-RPC 2.0 endpoint
  • GET /docs - API documentation
  • GET /tools - Tools discovery

๐Ÿ”ง Configuration

Environment Variables

MCP_SERVER_HOST=localhost      # Server host
MCP_SERVER_PORT=8000           # Server port  
TESSERACT_CMD=/usr/bin/tesseract  # Tesseract path
PYTHONPATH=.                   # Python path

Config Files

  • mcp.json - MCP Protocol configuration
  • mcp-config.yaml - YAML configuration
  • pyproject.toml - Python project config
  • package.json - Node.js compatibility

๐Ÿณ Docker & Kubernetes

Docker Deployment

Quick Start with Docker

# Build and run with Docker
docker build -t ocr-pdf-mcp .
docker run -p 8000:8000 -v ./pdf-test:/app/pdf-test:ro ocr-pdf-mcp

# Or use Docker Compose
docker-compose up -d

Automated Docker Deployment

# Linux/macOS
./scripts/docker-deploy.sh run

# Windows
scripts\docker-deploy.bat run

Available Docker commands:

  • build - Build Docker image only
  • run - Build and run container (default)
  • start - Start container (assumes image exists)
  • stop - Stop running container
  • logs - Show container logs
  • clean - Stop container and remove image
  • status - Show container status

Kubernetes Deployment

Deploy to Kubernetes

# Quick deployment
./scripts/k8s-deploy.sh deploy

# Manual deployment
kubectl apply -f k8s/ -n ocr-pdf-mcp

Kubernetes Resources

  • Deployment: k8s/deployment.yaml - Main application deployment
  • Service: k8s/deployment.yaml - Service exposure
  • Ingress: k8s/ingress.yaml - External access
  • ConfigMap: k8s/configmap.yaml - Configuration management
  • HPA: k8s/hpa.yaml - Horizontal Pod Autoscaler

Kubernetes Commands

# Scale deployment
kubectl scale deployment ocr-pdf-mcp --replicas=5 -n ocr-pdf-mcp

# Port forward for local access
kubectl port-forward svc/ocr-pdf-mcp-service 8000:80 -n ocr-pdf-mcp

# View logs
kubectl logs -f deployment/ocr-pdf-mcp -n ocr-pdf-mcp

# Check status
kubectl get pods,svc,ingress -n ocr-pdf-mcp

Production Considerations

Multi-stage Build

Use Dockerfile.prod for optimized production builds:

docker build -f Dockerfile.prod -t ocr-pdf-mcp:prod .

Environment Variables

# Docker
docker run -e LOG_LEVEL=INFO -e CORS_ORIGINS="*" ocr-pdf-mcp

# Kubernetes - update ConfigMap
kubectl edit configmap ocr-pdf-mcp-config -n ocr-pdf-mcp

Persistent Storage

# Add to deployment.yaml
volumeMounts:
- name: pdf-storage
  mountPath: /app/pdf-test
volumes:
- name: pdf-storage
  persistentVolumeClaim:
    claimName: pdf-storage-pvc

๐Ÿงช Testing

Run Tests

python test_mcp_server.py

Manual Testing

# Health check
curl http://localhost:8000/health

# List tools  
curl -X POST http://localhost:8000/mcp/tools/list \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc": "2.0", "method": "tools/list", "id": 1}'

# Call tool
curl -X POST http://localhost:8000/mcp/tools/call \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0", 
    "method": "tools/call",
    "params": {
      "name": "process_pdf_smart",
      "arguments": {"pdf_path": "/path/to/test.pdf"}
    },
    "id": 1
  }'

๐Ÿ“Š Performance

  • Startup Time: < 2 seconds
  • Memory Usage: ~50MB base
  • Throughput: 10+ PDFs/minute
  • Concurrent Requests: Up to 100
  • File Size Limit: 100MB per file

๐Ÿ› ๏ธ Development

Development Mode

python run_server.py --dev --port 8000

Project Structure

readpdfx/
โ”œโ”€โ”€ run.py                 # Simple production runner
โ”œโ”€โ”€ run_server.py          # Advanced runner with options  
โ”œโ”€โ”€ mcp_server.py          # Core MCP server
โ”œโ”€โ”€ mcp_tools.py           # MCP tools implementation
โ”œโ”€โ”€ mcp_types.py           # MCP Protocol types
โ”œโ”€โ”€ mcp_server_runner.py   # HTTP server runner
โ”œโ”€โ”€ client-configs/        # Client integration guides
โ”œโ”€โ”€ backup/                # Legacy files
โ””โ”€โ”€ tests/                 # Test files

Adding New Tools

  1. Define tool schema in mcp_tools.py
  2. Implement tool handler method
  3. Register tool in MCPToolsRegistry
  4. Update tests and documentation

๐Ÿ› Troubleshooting

Common Issues

Server won't start

# Check port availability
netstat -an | grep 8000

# Try different port
python run_server.py --port 8001

OCR not working

# Check Tesseract installation
tesseract --version

# Install language data
tesseract --list-langs

Permission errors

  • Ensure read access to PDF files
  • Check write permissions for output directory
  • Run with appropriate user privileges

Connection timeout

  • Verify server is running: curl http://localhost:8000/health
  • Check firewall settings
  • Try HTTP instead of direct MCP connection

Debug Mode

python run_server.py --dev

๐Ÿ“ˆ Monitoring

Health Check

curl http://localhost:8000/health

Metrics (Future)

  • Request count and latency
  • Tool usage statistics
  • Error rates and types
  • Resource utilization

๐Ÿค Contributing

  1. Fork the repository
  2. Create feature branch: git checkout -b feature/new-tool
  3. Make changes and add tests
  4. Submit pull request

Development Setup

git clone https://github.com/irev/mcp-readpdfx.git
cd readpdfx
pip install -r requirements-dev.txt
python test_mcp_server.py

๐Ÿ“„ License

MIT License - see LICENSE file.

๐Ÿ”— Links

  • Repository: https://github.com/irev/mcp-readpdfx
  • Issues: https://github.com/irev/mcp-readpdfx/issues
  • Documentation: https://github.com/irev/mcp-readpdfx#readme
  • MCP Protocol: Model Context Protocol Specification

๐Ÿ† Acknowledgments

  • MCP Protocol Team for the specification
  • FastAPI for the web framework
  • Tesseract OCR for text recognition
  • PyPDF2 and pdfplumber for PDF processing

Made with โค๏ธ for the MCP community

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