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:
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" } } } }
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 DomainnThis 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 contentproxy
: 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, incustom_proxy
: Your own proxy URL in “http://user:password@host:port” formatdevice
: Type of device emulation. Supported values: desktop, mobile, tableterror_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
- Fork the repository
- Create your feature branch
- Run tests:
npm test
- Submit a pull request
License
MIT License - see LICENSE file for details
WebScraping-AI MCP Server
Project Details
- webscraping-ai/webscraping-ai-mcp-server
- webscraping-ai-mcp
- Last Updated: 4/17/2025
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