crawl4ai-mcp-server

azure-architect/crawl4ai-mcp-server

3.3

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Crawl4AI MCP Server is a production-ready integration for the open-source, LLM-friendly web crawler, providing advanced web crawling and content extraction capabilities.

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Crawl4AI MCP Server

A production-ready Model Context Protocol (MCP) server integration for Crawl4AI - the open-source, LLM-friendly web crawler. This project provides seamless access to advanced web crawling and content extraction capabilities directly within Claude Desktop and Claude Code.

🚀 Quick Start

# Pull and run Crawl4AI
docker run -d -p 11235:11235 --name crawl4ai --shm-size=1g unclecode/crawl4ai:latest

# Add to Claude Desktop configuration
{
  "mcpServers": {
    "c4ai-sse": {
      "command": "sse",
      "args": ["http://localhost:11235/mcp/sse"]
    }
  }
}

That's it! You now have access to 7 powerful web crawling tools in Claude.

🛠 Available Tools

ToolDescriptionBest For
mdExtract clean markdown from web pagesBlog posts, articles, documentation
htmlExtract raw HTML contentWeb development, DOM analysis
screenshotCapture high-resolution screenshotsVisual verification, archival
pdfGenerate PDF from web pagesDocument archival, offline reading
execute_jsExecute JavaScript on pagesDynamic content, custom extraction
crawlBatch process multiple URLsHigh-volume scraping, comparisons
askQuery Crawl4AI's built-in knowledgeLibrary documentation, API reference

🎯 Key Features

  • Production Ready: Docker-based deployment with health checks and monitoring
  • LLM-Optimized: Content extraction specifically designed for AI consumption
  • High Performance: Concurrent processing with intelligent caching
  • Comprehensive: Screenshot capture, PDF generation, JavaScript execution
  • Reliable: Robust error handling and timeout management
  • Scalable: Kubernetes and cloud platform support

📊 Performance Highlights

From comprehensive testing across 7 tools:

  • Success Rate: 100% across all core functionality
  • Response Times: Average 2-8 seconds per request
  • Content Quality: Consistently clean, well-formatted output
  • Reliability: Robust handling of complex websites and edge cases
  • Concurrency: Efficient batch processing of multiple URLs

📚 Documentation

Core Documentation

  • - Complete installation instructions
  • - Detailed tool documentation with examples
  • - Production-ready code patterns and workflows
  • - Complete configuration options
  • - Diagnostic tools and common solutions
  • - Production deployment strategies

Quick Links

🔧 System Requirements

  • Docker: Version 20.10+
  • Memory: 2GB RAM minimum (4GB recommended)
  • Storage: 2GB free disk space
  • Network: Internet connectivity for image pull
  • Claude: Desktop or Code with MCP support

📦 Installation Methods

Method 1: Docker (Recommended)

# Basic installation
docker run -d \
  -p 11235:11235 \
  --name crawl4ai \
  --shm-size=1g \
  unclecode/crawl4ai:latest

Method 2: Docker Compose

version: '3.8'
services:
  crawl4ai:
    image: unclecode/crawl4ai:latest
    container_name: crawl4ai
    ports:
      - "11235:11235"
    shm_size: '1gb'
    restart: unless-stopped
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:11235/"]
      interval: 30s
      timeout: 10s
      retries: 3

Method 3: Kubernetes

apiVersion: apps/v1
kind: Deployment
metadata:
  name: crawl4ai
spec:
  replicas: 1
  selector:
    matchLabels:
      app: crawl4ai
  template:
    metadata:
      labels:
        app: crawl4ai
    spec:
      containers:
      - name: crawl4ai
        image: unclecode/crawl4ai:latest
        ports:
        - containerPort: 11235
        resources:
          requests:
            memory: "1Gi"
            cpu: "500m"
          limits:
            memory: "2Gi"
            cpu: "1"

🎨 Basic Usage

Extract Article Content

curl -X POST http://localhost:11235/md \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://en.wikipedia.org/wiki/Web_scraping",
    "f": "fit"
  }'

Capture Screenshots

curl -X POST http://localhost:11235/screenshot \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://github.com",
    "screenshot_wait_for": 3
  }'

Execute JavaScript

curl -X POST http://localhost:11235/execute_js \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://news.ycombinator.com",
    "scripts": [
      "Array.from(document.querySelectorAll(\".titleline a\")).slice(0, 5).map(a => ({title: a.textContent, url: a.href}))"
    ]
  }'

Batch Processing

curl -X POST http://localhost:11235/crawl \
  -H "Content-Type: application/json" \
  -d '{
    "urls": [
      "https://example.com",
      "https://httpbin.org/html",
      "https://jsonplaceholder.typicode.com"
    ]
  }'

🚀 Advanced Features

Custom Browser Configuration

{
  "url": "https://example.com",
  "browser_config": {
    "viewport_width": 1920,
    "viewport_height": 1080,
    "user_agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36",
    "headless": true
  }
}

Content Filtering Options

{
  "url": "https://example.com",
  "f": "fit",        // "raw", "fit", "bm25", "llm"
  "q": null,         // Query for bm25/llm filtering
  "c": "0"           // Content filtering level
}

JavaScript Execution Patterns

// Extract structured data
{
  title: document.title,
  headings: Array.from(document.querySelectorAll('h1,h2,h3')).map(h => h.textContent),
  links: Array.from(document.querySelectorAll('a')).slice(0, 10).map(a => ({
    text: a.textContent.trim(),
    url: a.href
  }))
}

🏭 Production Deployment

High Availability with Docker Swarm

docker service create \
  --name crawl4ai \
  --replicas 3 \
  --publish 11235:11235 \
  --mount type=volume,source=crawl4ai-cache,target=/app/cache \
  unclecode/crawl4ai:latest

Cloud Platform Deployment

AWS ECS, Google Cloud Run, Azure Container Instances - see for complete instructions.

Monitoring & Observability

# docker-compose.monitoring.yml
services:
  crawl4ai:
    image: unclecode/crawl4ai:latest
    environment:
      - METRICS_ENABLED=true
      - LOG_LEVEL=INFO
  
  prometheus:
    image: prom/prometheus
    ports:
      - "9090:9090"

🔍 Health Checks & Monitoring

# Basic health check
curl http://localhost:11235/

# Schema validation
curl http://localhost:11235/mcp/schema | jq '.tools | length'

# Performance monitoring
docker stats crawl4ai

🛡 Security Features

  • Network isolation with custom Docker networks
  • Resource limits to prevent resource exhaustion
  • Read-only containers for enhanced security
  • Non-root execution with proper user permissions

📈 Performance Tuning

Memory Optimization

docker run -d \
  --memory=4g \
  --memory-swap=4g \
  --shm-size=2g \
  --name crawl4ai \
  unclecode/crawl4ai:latest

CPU Optimization

docker run -d \
  --cpus="2.0" \
  --cpuset-cpus="0,1" \
  --name crawl4ai \
  unclecode/crawl4ai:latest

Browser Performance

{
  "browser_config": {
    "text_mode": true,
    "light_mode": true,
    "extra_args": [
      "--disable-images",
      "--disable-javascript",
      "--disable-plugins"
    ]
  }
}

🧪 Testing & Validation

Automated Testing Suite

# Run comprehensive tests
./test-crawl4ai.sh

# Expected results:
# 1. Health Check: ✓ PASS
# 2. Schema Check: ✓ PASS  
# 3. MD Tool Check: ✓ PASS
# 4. Screenshot Tool Check: ✓ PASS
# 5. JavaScript Tool Check: ✓ PASS

Manual Verification

# Test each tool individually
curl -X POST http://localhost:11235/md -H "Content-Type: application/json" -d '{"url": "https://example.com", "f": "fit"}'
curl -X POST http://localhost:11235/screenshot -H "Content-Type: application/json" -d '{"url": "https://example.com"}'
curl -X POST http://localhost:11235/execute_js -H "Content-Type: application/json" -d '{"url": "https://example.com", "scripts": ["document.title"]}'

🔧 Configuration

Environment Variables

# Logging
LOG_LEVEL=INFO              # DEBUG, INFO, WARNING, ERROR
MAX_WORKERS=4               # Maximum concurrent workers
TIMEOUT=30                  # Default request timeout

# Features  
CACHE_ENABLED=true          # Enable caching
SCREENSHOT_ENABLED=true     # Enable screenshots
PDF_ENABLED=true            # Enable PDF generation

# Security
RATE_LIMIT=100              # Requests per minute
MAX_URL_LENGTH=2048         # Maximum URL length

Claude Desktop Integration

{
  "mcpServers": {
    "c4ai-sse": {
      "command": "sse",
      "args": ["http://localhost:11235/mcp/sse"],
      "env": {
        "LOG_LEVEL": "INFO",
        "TIMEOUT": "30"
      }
    }
  }
}

📊 Use Cases

Content Analysis Pipeline

def comprehensive_analysis(url):
    # Step 1: Extract content
    md_result = call_tool("md", {"url": url, "f": "fit"})
    
    # Step 2: Analyze structure  
    js_result = call_tool("execute_js", {
        "url": url,
        "scripts": ["({wordCount: document.body.textContent.split(' ').length})"]
    })
    
    # Step 3: Visual verification
    screenshot_result = call_tool("screenshot", {"url": url})
    
    return combine_results(md_result, js_result, screenshot_result)

Competitive Monitoring

def monitor_competitors(urls):
    # Batch process all competitors
    batch_result = call_tool("crawl", {"urls": urls})
    
    # Extract pricing and product info
    for result in batch_result["results"]:
        if result["success"]:
            analyze_competitor_data(result)

🚨 Troubleshooting

Common Issues

IssueSolution
Port already in useUse -p 8080:11235 for alternative port
Container won't startCheck docker logs crawl4ai for errors
MCP connection failedVerify endpoint with curl http://localhost:11235/mcp/sse
High memory usageAdd --memory=4g --shm-size=2g limits
Request timeoutsIncrease timeout in tool parameters

Diagnostic Commands

# Container status
docker ps | grep crawl4ai
docker inspect crawl4ai --format='{{.State.Health.Status}}'

# Network connectivity
curl -I http://localhost:11235/
telnet localhost 11235

# Resource usage
docker stats crawl4ai

🤝 Contributing

This is a deployment and integration project for the open-source Crawl4AI library. For core Crawl4AI development:

For MCP integration issues or deployment improvements, please open an issue in this repository.

📄 License

This project follows the licensing of the underlying Crawl4AI project. Please refer to the official Crawl4AI repository for license information.

🙏 Acknowledgments

  • Crawl4AI Team - For creating the excellent open-source web crawling library
  • Anthropic - For the Model Context Protocol specification and Claude integration
  • Community Contributors - For testing, feedback, and improvements

📞 Support

  • Documentation: Comprehensive guides in the /docs directory
  • Issues: Report problems via GitHub Issues
  • Community: Join discussions in the Crawl4AI community
  • Commercial: Contact for enterprise support and custom deployments

🎉 Ready to start crawling? Follow the Quick Start guide above or dive into the for detailed instructions.

Last updated: August 4, 2025
Version: 1.0.0