Webscraper MCP Server

The Webscraper MCP addresses a common bottleneck for AI assistants: the ability to fetch and understand content that resides outside of their training data. By exposing a set of lightweight, well‑defined tools, this server lets Claude (or any MCP‑compatible client) pull raw text from arbitrary web pages, YouTube videos, and PDF documents with a single function call. The result is richer, up‑to‑date knowledge that can be queried in real time without compromising the security model of the host application.

At its core, the server offers three distinct extraction tools.

• retrieves the visible text from any standard HTML page, enabling the assistant to answer questions about news articles, blog posts, or documentation that are not part of its static knowledge base.
• pulls the auto‑generated or provided transcript from a YouTube video, allowing users to ask detailed questions about lecture videos, tutorials, or interviews.
• converts a PDF file located at a public URL into Markdown‑formatted text, making it trivial to analyze research papers, reports, or technical specifications.

These tools are intentionally minimalistic: each accepts a single URL argument and returns plain text, keeping the interface straightforward for developers to integrate. Because the server runs locally on a user’s machine (e.g., Claude Desktop), it respects privacy constraints while still providing instant access to external content.

Typical use cases include:

• Research assistants that need up‑to‑date market reports or academic papers.
• Content creators who want to pull data from web pages or videos for summarization, translation, or fact‑checking.
• Enterprise knowledge bases that must ingest PDFs and web pages into internal AI workflows without manual copy‑paste.
• Educational tools that transform lecture videos into searchable transcripts for students.

Integration is seamless: a developer simply declares the MCP server in their client configuration, and Claude can invoke any of the three tools via natural language prompts. The server’s responses are returned as plain text, which can then be parsed or fed into downstream models for summarization, sentiment analysis, or question answering.

What sets Webscraper apart is its focus on simplicity and security. By limiting itself to three well‑documented endpoints, it reduces attack surface while still offering powerful content extraction. The server’s certification by MCPReview further assures developers that it adheres to community standards for reliability and safety. For teams building AI‑driven workflows that depend on real‑world data, Webscraper provides a reliable bridge between the web and the assistant’s internal reasoning engine.