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webscraping-ai/webscraping-ai-mcp-server

by Various

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

W

MCP

webscraping-ai/webscraping-ai-mcp-server

Added 1 June 2026

Overview

Implements the Model Context Protocol (MCP) to let AI applications use WebScraping.AI for web data extraction. It acts as a server that handles requests from MCP clients, returning scraped content through the WebScraping.AI API.

Best for

Best for
Developers building MCP-based AI applications that need reliable, API-driven web scraping

Use cases

  • Extract structured data from websites for AI analysis or knowledge bases
  • Scrape web content on demand from within MCP-compatible assistants or agents
  • Automate data collection tasks by plugging into MCP-based workflows

How to use

Install

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

Tested with

Cursor, Claude Desktop

Example client config

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

Notes

Implements the Model Context Protocol (MCP) to let AI applications use WebScraping.AI for web data extraction. It acts as a server that handles requests from MCP clients, returning scraped content through the WebScraping.AI API.

42 stars on GitHub. Last updated 2026-05-12.

Use cases

  • Extract structured data from websites for AI analysis or knowledge bases
  • Scrape web content on demand from within MCP-compatible assistants or agents
  • Automate data collection tasks by plugging into MCP-based workflows

Pros

  • Leverages the standardized MCP interface for seamless integration with MCP clients
  • Abstracts away the complexity of WebScraping.AI’s API behind a simple protocol
  • Lightweight JavaScript implementation easy to deploy in Node.js environments

Cons

  • Depends entirely on the WebScraping.AI service and its API availability and pricing
  • Small community and limited documentation given only 42 GitHub stars
  • Requires an API key and internet access to function, limiting offline use

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Leverages the standardized MCP interface for seamless integration with MCP clients
  • Abstracts away the complexity of WebScraping.AI's API behind a simple protocol
  • Lightweight JavaScript implementation easy to deploy in Node.js environments

Cons

  • Depends entirely on the WebScraping.AI service and its API availability and pricing
  • Small community and limited documentation given only 42 GitHub stars
  • Requires an API key and internet access to function, limiting offline use
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