webscraping-ai/webscraping-ai-mcp-server

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

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.