What are the best n8n integrations for web scraping projects?

n8n offers a comprehensive ecosystem of integrations specifically designed for web scraping workflows. The platform combines native nodes with third-party API integrations to create powerful, automated scraping pipelines. This guide explores the best n8n integrations for building robust web scraping projects.

Core n8n Nodes for Web Scraping

1. HTTP Request Node

The HTTP Request node is the foundation of most web scraping workflows in n8n. It allows you to make GET, POST, and other HTTP requests to fetch web pages and interact with APIs.

Key Features: - Support for all HTTP methods (GET, POST, PUT, DELETE, etc.) - Custom headers and authentication options - JSON and XML response parsing - Cookie management - Proxy support

Example Configuration:

{
  "method": "GET",
  "url": "https://example.com/products",
  "options": {
    "headers": {
      "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"
    },
    "timeout": 30000,
    "followRedirect": true
  }
}

2. HTML Extract Node

The HTML Extract node provides a visual interface for extracting data from HTML pages using CSS selectors or XPath expressions.

Use Cases: - Extracting product information from e-commerce sites - Scraping article content from news websites - Collecting structured data from listings

Example CSS Selector Extraction:

{
  "extractionValues": {
    "title": {
      "selector": "h1.product-title",
      "returnValue": "text"
    },
    "price": {
      "selector": ".price-value",
      "returnValue": "text"
    },
    "image": {
      "selector": "img.product-image",
      "returnValue": "attribute",
      "attributeName": "src"
    }
  }
}

3. Puppeteer Node

The Puppeteer node enables headless browser automation, making it ideal for scraping JavaScript-rendered websites and handling dynamic content that requires browser execution.

Advanced Capabilities: - Execute JavaScript on pages - Take screenshots - Generate PDFs - Handle authentication flows - Wait for dynamic content to load

Example Puppeteer Workflow:

// Navigate and extract data
const page = await browser.newPage();
await page.goto('https://example.com/products');

// Wait for content to load
await page.waitForSelector('.product-list');

// Extract data
const products = await page.evaluate(() => {
  return Array.from(document.querySelectorAll('.product-item')).map(item => ({
    name: item.querySelector('.product-name')?.textContent,
    price: item.querySelector('.product-price')?.textContent,
    availability: item.querySelector('.stock-status')?.textContent
  }));
});

return products;

4. Code Node (JavaScript)

The Code node allows you to write custom JavaScript for complex data transformation and scraping logic that native nodes can't handle.

Python Alternative:

For Python developers, n8n also supports Python in the Code node:

import re
from datetime import datetime

# Process scraped data
for item in items:
    # Clean price data
    price_text = item['price']
    price_value = float(re.sub(r'[^0-9.]', '', price_text))

    # Add timestamp
    item['scraped_at'] = datetime.now().isoformat()

    # Calculate discount
    if 'original_price' in item:
        original = float(re.sub(r'[^0-9.]', '', item['original_price']))
        item['discount_percentage'] = round((1 - price_value/original) * 100, 2)

return items

Third-Party API Integrations

5. WebScraping.AI Integration

WebScraping.AI provides a powerful API that handles JavaScript rendering, proxy rotation, and CAPTCHA solving automatically. It's one of the most reliable integrations for production-level scraping.

Integration Setup:

# Using HTTP Request node with WebScraping.AI
curl -X GET "https://api.webscraping.ai/html" \
  -H "api_key: YOUR_API_KEY" \
  -d "url=https://example.com" \
  -d "js=true" \
  -d "proxy=datacenter"

n8n HTTP Request Configuration:

{
  "method": "GET",
  "url": "https://api.webscraping.ai/html",
  "authentication": "headerAuth",
  "headerAuth": {
    "name": "api_key",
    "value": "={{$credentials.webScrapingAiApiKey}}"
  },
  "queryParameters": {
    "url": "={{$json.targetUrl}}",
    "js": "true",
    "proxy": "residential"
  }
}

Benefits: - Built-in JavaScript rendering - Automatic proxy rotation - CAPTCHA solving - AI-powered data extraction - High success rates

6. ScrapingBee Integration

ScrapingBee offers headless browser capabilities and proxy management through a simple API interface.

Example Implementation:

// Using Code node with ScrapingBee
const axios = require('axios');

const response = await axios.get('https://app.scrapingbee.com/api/v1/', {
  params: {
    'api_key': 'YOUR_API_KEY',
    'url': 'https://example.com',
    'render_js': 'true',
    'premium_proxy': 'true'
  }
});

return response.data;

7. Bright Data (formerly Luminati) Integration

Bright Data provides enterprise-grade proxy networks and web scraping infrastructure.

Key Features: - Residential, datacenter, and mobile proxies - CAPTCHA solving - Browser automation - API endpoints for common scraping tasks

8. Cheerio (via Code Node)

While Cheerio isn't a standalone integration, it's commonly used within n8n's Code node for efficient HTML parsing.

Installation in n8n:

# Add to your n8n instance's package.json
npm install cheerio

Usage Example:

const cheerio = require('cheerio');

// Load HTML
const $ = cheerio.load(html);

// Extract data efficiently
const products = [];
$('.product-card').each((i, element) => {
  products.push({
    name: $(element).find('.product-name').text().trim(),
    price: $(element).find('.price').text().trim(),
    rating: $(element).find('.rating').attr('data-rating'),
    url: $(element).find('a').attr('href')
  });
});

return products;

Database and Storage Integrations

9. Google Sheets Integration

Store scraped data directly in Google Sheets for easy sharing and analysis.

Workflow Example: 1. HTTP Request to fetch data 2. HTML Extract to parse content 3. Google Sheets node to append rows

10. PostgreSQL/MySQL Integration

For large-scale scraping projects, database integrations provide robust data storage.

-- Example schema for scraped products
CREATE TABLE scraped_products (
  id SERIAL PRIMARY KEY,
  product_name VARCHAR(255),
  price DECIMAL(10, 2),
  url TEXT,
  scraped_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

11. Airtable Integration

Airtable combines spreadsheet simplicity with database power, perfect for organizing scraped data.

Notification and Monitoring Integrations

12. Slack Integration

Receive real-time notifications about scraping job status and errors.

{
  "channel": "#scraping-alerts",
  "text": "Scraping job completed: {{$json.recordsScraped}} records extracted",
  "attachments": [
    {
      "color": "good",
      "fields": [
        {
          "title": "Duration",
          "value": "{{$json.duration}} seconds"
        }
      ]
    }
  ]
}

13. Discord Integration

Alternative to Slack for team notifications and workflow monitoring.

14. Email Integration

Send automated reports and error notifications via SMTP or email service providers.

Scheduling and Automation Integrations

15. Cron Node

Schedule scraping tasks to run automatically at specified intervals.

# Run daily at 3 AM
0 3 * * *

# Run every 6 hours
0 */6 * * *

# Run every Monday at 9 AM
0 9 * * 1

16. Webhook Node

Trigger scraping workflows via HTTP webhooks from external applications.

Best Practices for Integration Selection

Choose Based on Target Website Complexity

Static HTML Sites: - HTTP Request + HTML Extract - Fast and resource-efficient - No JavaScript execution needed

Dynamic JavaScript Sites: - Puppeteer node - WebScraping.AI API - Proper handling of AJAX requests is crucial

Complex Sites with Anti-Bot Protection: - WebScraping.AI - ScrapingBee - Bright Data with residential proxies

Consider Scale and Performance

Small Projects (< 1000 pages/day): - Native n8n nodes (HTTP Request, HTML Extract) - Self-hosted Puppeteer

Medium Projects (1000-10000 pages/day): - WebScraping.AI API - ScrapingBee - Proxy rotation

Large Projects (> 10000 pages/day): - Enterprise API solutions (Bright Data) - Distributed scraping architecture - Database storage integration

Monitoring and Error Handling

Implement robust error handling in your workflows:

try {
  // Scraping logic
  const data = await scrapePage(url);
  return { success: true, data };
} catch (error) {
  // Log error
  console.error('Scraping failed:', error);

  // Send notification
  await sendSlackAlert({
    message: 'Scraping failed',
    url: url,
    error: error.message
  });

  // Return error state
  return { success: false, error: error.message };
}

Sample Complete Workflow

Here's a production-ready n8n workflow combining multiple integrations:

{
  "nodes": [
    {
      "name": "Schedule Daily",
      "type": "n8n-nodes-base.cron",
      "parameters": {
        "triggerTimes": {
          "item": [{"hour": 3, "minute": 0}]
        }
      }
    },
    {
      "name": "Fetch Page",
      "type": "n8n-nodes-base.httpRequest",
      "parameters": {
        "url": "https://api.webscraping.ai/html",
        "options": {
          "qs": {
            "url": "https://example.com/products",
            "js": "true"
          }
        }
      }
    },
    {
      "name": "Extract Data",
      "type": "n8n-nodes-base.htmlExtract",
      "parameters": {
        "extractionValues": {
          "products": {
            "cssSelector": ".product-item"
          }
        }
      }
    },
    {
      "name": "Save to Database",
      "type": "n8n-nodes-base.postgres",
      "parameters": {
        "operation": "insert",
        "table": "products"
      }
    },
    {
      "name": "Notify Completion",
      "type": "n8n-nodes-base.slack",
      "parameters": {
        "channel": "#scraping",
        "text": "Scraping completed successfully"
      }
    }
  ]
}

Conclusion

The best n8n integrations for web scraping depend on your project requirements, target website complexity, and scale. Start with native nodes like HTTP Request and HTML Extract for simple projects, then add Puppeteer for JavaScript-heavy sites. For production environments, integrate specialized APIs like WebScraping.AI for reliability and scale. Combine these with proper storage (databases, Google Sheets) and monitoring (Slack, email) integrations to build robust, maintainable scraping workflows.

Remember to respect websites' terms of service and implement rate limiting to ensure ethical and sustainable scraping practices.