Fetches and extracts clean, AI-optimized web content, delivering it in a structured markdown format.
Sponsored
This Model Context Protocol (MCP) server is engineered to streamline web content acquisition and extraction, primarily for AI agents. It leverages the Trafilatura library to intelligently fetch webpages, remove boilerplate elements like navigation bars, advertisements, and footers, and deliver pristine markdown output. Beyond basic content fetching, FetchV2 supports batch processing for retrieving content from multiple URLs in a single request and offers robust link discovery capabilities with filtering, ensuring AI models receive high-quality, relevant information efficiently.
Key Features
01Complies with robots.txt rules and includes graceful timeout handling.
02Offers pagination support for large pages using a start index.
03Extracts clean markdown content from any URL, removing boilerplate.
04Discovers and filters links on webpages for targeted exploration.
05Supports batch fetching of up to 10 URLs in a single request.
060 GitHub stars
Use Cases
01Automatically fetch documentation or articles for AI agent analysis.
02Discover and filter related links on a webpage for targeted research.
03Summarize differences across multiple web pages by batch fetching their content.
