Webscraping AI MCP Server

What is Webscraping AI MCP Server about?

Webscraping AI MCP Server implements a set of MCP‑compatible tools that enable LLMs and other clients to retrieve and interpret web content on demand. It supports answering questions about pages, extracting structured fields, fetching full HTML (with optional JavaScript rendering), pulling visible text, and selecting content via CSS selectors. The server also offers proxy rotation, device emulation, custom JavaScript injection, and account‑usage monitoring.

How to use Webscraping AI MCP Server?

1. Run the server (quick start):

   env WEBSCRAPING_AI_API_KEY=your_api_key npx -y webscraping-ai-mcp
   

2. Configure for Cursor or Claude Desktop by adding a .cursor/mcp.json or claude_desktop_config.json that points to the npx command and supplies the required environment variables (API key, optional concurrency limit, etc.).
3. Invoke tools through the MCP client by sending JSON payloads matching the tool definitions (e.g., webscraping_ai_question, webscraping_ai_fields, webscraping_ai_html, etc.).
4. Handle responses which contain a content array and an isError flag.

Key features of Webscraping AI MCP Server

• Question answering about any web page
• Structured data extraction using user‑defined field instructions
• Full HTML retrieval with headless Chrome/Chromium rendering
• Plain‑text extraction of visible content
• CSS selector‑based single or multiple element extraction
• Proxy support (datacenter or residential) with country selection
• Device emulation (desktop, mobile, tablet)
• Custom JavaScript execution on target pages
• Concurrency limit and rate‑limit handling
• Account usage statistics tool
• Robust error handling with automatic retries and back‑off

Use cases of Webscraping AI MCP Server

• Enabling LLM agents to browse the web for up‑to‑date information
• Automatically pulling product catalogs, prices, and descriptions for e‑commerce monitoring
• Collecting news articles, blogs, or research papers for summarization
• Scraping dynamic sites that require JavaScript execution or waiting for specific DOM elements
• Performing geographic‑specific data collection via proxy country selection
• Integrating web‑derived data into downstream AI workflows (e.g., content generation, fact‑checking)

FAQ from the Webscraping AI MCP Server

Q: What environment variable is mandatory?

• WEBSCRAPING_AI_API_KEY must be set to a valid Webscraping.AI API key.

Q: Can I change the default concurrency?

• Yes, set WEBSCRAPING_AI_CONCURRENCY_LIMIT (default is 5).

Q: How do I disable JavaScript rendering?

• Set WEBSCRAPING_AI_DEFAULT_JS_RENDERING=false or pass "js": false in the tool arguments.

Q: Which proxy types are available?

• datacenter and residential (default is residential).

Q: How do I specify a custom proxy URL?

• Use the custom_proxy argument with a URL like http://user:pass@host:port.

Q: What is the maximum timeout for page retrieval?

• Up to 30 000 ms (configurable via WEBSCRAPING_AI_DEFAULT_TIMEOUT).

Q: Is there a way to get account usage information?

• Yes, the webscraping_ai_account tool returns requests made, remaining quota, limits, and reset time.

Q: How can I run the server on Windows if I encounter issues?

• Use the command cmd /c "set WEBSCRAPING_AI_API_KEY=your-api-key && npx -y webscraping-ai-mcp".

WebScraping.AI MCP Server

A Model Context Protocol (MCP) server implementation that integrates with WebScraping.AI for web data extraction capabilities.

Features

• Question answering about web page content
• Structured data extraction from web pages
• HTML content retrieval with JavaScript rendering
• Plain text extraction from web pages
• CSS selector-based content extraction
• Multiple proxy types (datacenter, residential) with country selection
• JavaScript rendering using headless Chrome/Chromium
• Concurrent request management with rate limiting
• Custom JavaScript execution on target pages
• Device emulation (desktop, mobile, tablet)
• Account usage monitoring

Installation

Running with npx

env WEBSCRAPING_AI_API_KEY=your_api_key npx -y webscraping-ai-mcp

Manual Installation

# Clone the repository
git clone https://github.com/webscraping-ai/webscraping-ai-mcp-server.git
cd webscraping-ai-mcp-server

# Install dependencies
npm install

# Run
npm start

Configuring in Cursor

Note: Requires Cursor version 0.45.6+

The WebScraping.AI MCP server can be configured in two ways in Cursor:

1. Project-specific Configuration (recommended for team projects): Create a .cursor/mcp.json file in your project directory:

   {
     "servers": {
       "webscraping-ai": {
         "type": "command",
         "command": "npx -y webscraping-ai-mcp",
         "env": {
           "WEBSCRAPING_AI_API_KEY": "your-api-key",
           "WEBSCRAPING_AI_CONCURRENCY_LIMIT": "5"
         }
       }
     }
   }
   

2. Global Configuration (for personal use across all projects): Create a ~/.cursor/mcp.json file in your home directory with the same configuration format as above.

If you are using Windows and are running into issues, try using cmd /c "set WEBSCRAPING_AI_API_KEY=your-api-key && npx -y webscraping-ai-mcp" as the command.

This configuration will make the WebScraping.AI tools available to Cursor's AI agent automatically when relevant for web scraping tasks.

Running on Claude Desktop

Add this to your claude_desktop_config.json:

{
  "mcpServers": {
    "mcp-server-webscraping-ai": {
      "command": "npx",
      "args": ["-y", "webscraping-ai-mcp"],
      "env": {
        "WEBSCRAPING_AI_API_KEY": "YOUR_API_KEY_HERE",
        "WEBSCRAPING_AI_CONCURRENCY_LIMIT": "5"
      }
    }
  }
}

Configuration

Environment Variables

Required

• WEBSCRAPING_AI_API_KEY: Your WebScraping.AI API key
  • Required for all operations
  • Get your API key from WebScraping.AI

Optional Configuration

• WEBSCRAPING_AI_CONCURRENCY_LIMIT: Maximum number of concurrent requests (default: 5)
• WEBSCRAPING_AI_DEFAULT_PROXY_TYPE: Type of proxy to use (default: residential)
• WEBSCRAPING_AI_DEFAULT_JS_RENDERING: Enable/disable JavaScript rendering (default: true)
• WEBSCRAPING_AI_DEFAULT_TIMEOUT: Maximum web page retrieval time in ms (default: 15000, max: 30000)
• WEBSCRAPING_AI_DEFAULT_JS_TIMEOUT: Maximum JavaScript rendering time in ms (default: 2000)

Configuration Examples

For standard usage:

# Required
export WEBSCRAPING_AI_API_KEY=your-api-key

# Optional - customize behavior (default values)
export WEBSCRAPING_AI_CONCURRENCY_LIMIT=5
export WEBSCRAPING_AI_DEFAULT_PROXY_TYPE=residential # datacenter or residential
export WEBSCRAPING_AI_DEFAULT_JS_RENDERING=true
export WEBSCRAPING_AI_DEFAULT_TIMEOUT=15000
export WEBSCRAPING_AI_DEFAULT_JS_TIMEOUT=2000

Available Tools

1. Question Tool (webscraping_ai_question)

Ask questions about web page content.

{
  "name": "webscraping_ai_question",
  "arguments": {
    "url": "https://example.com",
    "question": "What is the main topic of this page?",
    "timeout": 30000,
    "js": true,
    "js_timeout": 2000,
    "wait_for": ".content-loaded",
    "proxy": "datacenter",
    "country": "us"
  }
}

Example response:

{
  "content": [
    {
      "type": "text",
      "text": "The main topic of this page is examples and documentation for HTML and web standards."
    }
  ],
  "isError": false
}

2. Fields Tool (webscraping_ai_fields)

Extract structured data from web pages based on instructions.

{
  "name": "webscraping_ai_fields",
  "arguments": {
    "url": "https://example.com/product",
    "fields": {
      "title": "Extract the product title",
      "price": "Extract the product price",
      "description": "Extract the product description"
    },
    "js": true,
    "timeout": 30000
  }
}

Example response:

{
  "content": [
    {
      "type": "text",
      "text": {
        "title": "Example Product",
        "price": "$99.99",
        "description": "This is an example product description."
      }
    }
  ],
  "isError": false
}

3. HTML Tool (webscraping_ai_html)

Get the full HTML of a web page with JavaScript rendering.

{
  "name": "webscraping_ai_html",
  "arguments": {
    "url": "https://example.com",
    "js": true,
    "timeout": 30000,
    "wait_for": "#content-loaded"
  }
}

Example response:

{
  "content": [
    {
      "type": "text",
      "text": "<html>...[full HTML content]...</html>"
    }
  ],
  "isError": false
}

4. Text Tool (webscraping_ai_text)

Extract the visible text content from a web page.

{
  "name": "webscraping_ai_text",
  "arguments": {
    "url": "https://example.com",
    "js": true,
    "timeout": 30000
  }
}

Example response:

{
  "content": [
    {
      "type": "text",
      "text": "Example Domain\nThis domain is for use in illustrative examples in documents..."
    }
  ],
  "isError": false
}

5. Selected Tool (webscraping_ai_selected)

Extract content from a specific element using a CSS selector.

{
  "name": "webscraping_ai_selected",
  "arguments": {
    "url": "https://example.com",
    "selector": "div.main-content",
    "js": true,
    "timeout": 30000
  }
}

Example response:

{
  "content": [
    {
      "type": "text",
      "text": "<div class=\"main-content\">This is the main content of the page.</div>"
    }
  ],
  "isError": false
}

6. Selected Multiple Tool (webscraping_ai_selected_multiple)

Extract content from multiple elements using CSS selectors.

{
  "name": "webscraping_ai_selected_multiple",
  "arguments": {
    "url": "https://example.com",
    "selectors": ["div.header", "div.product-list", "div.footer"],
    "js": true,
    "timeout": 30000
  }
}

Example response:

{
  "content": [
    {
      "type": "text",
      "text": [
        "<div class=\"header\">Header content</div>",
        "<div class=\"product-list\">Product list content</div>",
        "<div class=\"footer\">Footer content</div>"
      ]
    }
  ],
  "isError": false
}

7. Account Tool (webscraping_ai_account)

Get information about your WebScraping.AI account.

{
  "name": "webscraping_ai_account",
  "arguments": {}
}

Example response:

{
  "content": [
    {
      "type": "text",
      "text": {
        "requests": 5000,
        "remaining": 4500,
        "limit": 10000,
        "resets_at": "2023-12-31T23:59:59Z"
      }
    }
  ],
  "isError": false
}

Common Options for All Tools

The following options can be used with all scraping tools:

• timeout: Maximum web page retrieval time in ms (15000 by default, maximum is 30000)
• js: Execute on-page JavaScript using a headless browser (true by default)
• js_timeout: Maximum JavaScript rendering time in ms (2000 by default)
• wait_for: CSS selector to wait for before returning the page content
• proxy: Type of proxy, datacenter or residential (residential by default)
• country: Country of the proxy to use (US by default). Supported countries: us, gb, de, it, fr, ca, es, ru, jp, kr, in
• custom_proxy: Your own proxy URL in "http://user:password@host:port" format
• device: Type of device emulation. Supported values: desktop, mobile, tablet
• error_on_404: Return error on 404 HTTP status on the target page (false by default)
• error_on_redirect: Return error on redirect on the target page (false by default)
• js_script: Custom JavaScript code to execute on the target page

Error Handling

The server provides robust error handling:

• Automatic retries for transient errors
• Rate limit handling with backoff
• Detailed error messages
• Network resilience

Example error response:

{
  "content": [
    {
      "type": "text",
      "text": "API Error: 429 Too Many Requests"
    }
  ],
  "isError": true
}

Integration with LLMs

This server implements the Model Context Protocol, making it compatible with any MCP-enabled LLM platforms. You can configure your LLM to use these tools for web scraping tasks.

Example: Configuring Claude with MCP

const { Claude } = require('@anthropic-ai/sdk');
const { Client } = require('@modelcontextprotocol/sdk/client/index.js');
const { StdioClientTransport } = require('@modelcontextprotocol/sdk/client/stdio.js');

const claude = new Claude({
  apiKey: process.env.ANTHROPIC_API_KEY
});

const transport = new StdioClientTransport({
  command: 'npx',
  args: ['-y', 'webscraping-ai-mcp'],
  env: {
    WEBSCRAPING_AI_API_KEY: 'your-api-key'
  }
});

const client = new Client({
  name: 'claude-client',
  version: '1.0.0'
});

await client.connect(transport);

// Now you can use Claude with WebScraping.AI tools
const tools = await client.listTools();
const response = await claude.complete({
  prompt: 'What is the main topic of example.com?',
  tools: tools
});

Development

# Clone the repository
git clone https://github.com/webscraping-ai/webscraping-ai-mcp-server.git
cd webscraping-ai-mcp-server

# Install dependencies
npm install

# Run tests
npm test

# Add your .env file
cp .env.example .env

# Start the inspector
npx @modelcontextprotocol/inspector node src/index.js

Contributing

1. Fork the repository
2. Create your feature branch
3. Run tests: npm test
4. Submit a pull request

License

MIT License - see LICENSE file for details