by egoist
Fetch is a web scraping tool that extracts web content and YouTube transcripts, converting HTML to Markdown with accurat
Fetches web pages and YouTube video transcripts, converting HTML content to readable Markdown format for analysis and reference.
You can install Fetch (Web Content & YouTube Transcripts) in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
Fetch (Web Content & YouTube Transcripts) is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Fetch and extract information from websites automatically
Example
Research competitor pricing, scrape product reviews, monitor news mentions
Automate 5-10 hours/week of manual web research
Track website changes, new content, price updates
Example
Monitor competitor blog for new posts, track stock availability, watch for pricing changes
Stay informed without manual checking, never miss important updates
Extract structured data from multiple websites
Example
Compile product listings from 10 e-commerce sites, aggregate job postings, collect real estate data
Build datasets 100x faster than manual copying
Share your MCP server with the developer community
We evaluated Fetch (Web Content & YouTube Transcripts) against two servers with overlapping tools; this profile had the clearer scope statement.
Fetch (Web Content & YouTube Transcripts) reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
Fetch (Web Content & YouTube Transcripts) has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
We wired Fetch (Web Content & YouTube Transcripts) into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Fetch (Web Content & YouTube Transcripts) is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
According to our notes, Fetch (Web Content & YouTube Transcripts) benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Fetch (Web Content & YouTube Transcripts) has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
I recommend Fetch (Web Content & YouTube Transcripts) for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Fetch (Web Content & YouTube Transcripts) is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
We wired Fetch (Web Content & YouTube Transcripts) into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
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An MCP server for fetching URLs / Youtube video transcript.
This project is sponsored by ChatWise, an all-in-one LLM chatbot with first-class MCP support.
# stdio server
npx -y fetch-mcp
# sse server
npx -y fetch-mcp --sse
# streamable http server at /mcp
npx -y fetch-mcp --http
# custom endpoint
npx -y fetch-mcp --http /my-mcp
Fetch URL, can return HTML or Markdown (default).
Fetch Youtube transcript.
MIT. ","githubUrl":"https://github.com/egoist/fetch-mcp"}] 1f:null
Interact with services that don't offer APIs
Example
Check form submissions, validate website functionality, test user flows
Automate interactions with any website, even without API
Prerequisites
Time Estimate
20-40 minutes including configuration and testing
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
MCP server handles HTTP requests, HTML parsing, JavaScript rendering (if headless browser), and returns structured data to Claude.
Protocols
Compatibility
✓ Use when
Use for research automation, content monitoring, data aggregation from multiple sources, and when official APIs don't exist. Best for read-only information gathering.
✗ Avoid when
Avoid for sites with APIs (use API instead), sites that explicitly forbid scraping, when data is copyrighted, or for login-required content without proper authorization.