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Fetch (Web Content & YouTube Transcripts)▌

egoist

by egoist

Fetch is a web scraping tool that extracts web content and YouTube transcripts, converting HTML to Markdown with accurat

Fetches web content and YouTube video transcripts, converting HTML to Markdown and extracting timestamps for reference in conversations.

github stars

★ 157

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0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

No API key neededAutomatic HTML to Markdown conversion

best for

  • / Research and content analysis
  • / Creating summaries from web articles
  • / Extracting YouTube video content for notes

capabilities

  • / Fetch web pages and convert HTML to Markdown
  • / Extract YouTube video transcripts with timestamps
  • / Retrieve text content from URLs
  • / Process image content from web pages

what it does

Fetches web pages and YouTube video transcripts, converting HTML content to readable Markdown format for analysis and reference.

how to install

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.

license

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.

readme

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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.

Usage

# 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

Tools

fetch_url

Fetch URL, can return HTML or Markdown (default).

fetch_youtube_transcript

Fetch Youtube transcript.

License

MIT. ","githubUrl":"https://github.com/egoist/fetch-mcp"}] 1f:null

FAQ

What is the Fetch (Web Content & YouTube Transcripts) MCP server?
Fetch (Web Content & YouTube Transcripts) is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Fetch (Web Content & YouTube Transcripts)?
This profile displays 54 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.8 out of 5—verify behavior in your own environment before production use.

Use Cases▌

Web Research & Information Gathering

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

Content Monitoring & Alerts

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

Data Extraction & Aggregation

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

API-less Integration

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

Implementation Guide▌

Prerequisites

  • ›Claude Desktop or Cursor with MCP support
  • ›Understanding of web scraping ethics and robots.txt
  • ›Rate limiting awareness to avoid overwhelming target sites
  • ›Knowledge of legal restrictions on data collection

Time Estimate

20-40 minutes including configuration and testing

Installation Steps

  1. 1.Install web automation MCP server via npm or pip
  2. 2.Configure allowed domains and rate limits in MCP config
  3. 3.Test with simple fetch: 'Get content from example.com'
  4. 4.Progress to extraction: 'Extract all product prices from this page'
  5. 5.Set up monitoring: 'Check this URL daily for changes'
  6. 6.Parse structured data: 'Create CSV from this table'
  7. 7.Respect robots.txt and rate limits always

Troubleshooting

  • ⚠403 Forbidden: Website blocks bots—respect their wishes, use official API instead
  • ⚠Rate limit errors: Slow down requests, add delays between fetches
  • ⚠Stale data: Target site changed HTML structure—update selectors
  • ⚠Timeout errors: Site is slow or blocking—increase timeout, try different user agent
  • ⚠JavaScript-rendered content: Use headless browser MCP servers for dynamic sites

Best Practices▌

✓ Do

  • +Check robots.txt and respect crawl rules
  • +Rate limit requests: 1-2 requests/second maximum
  • +Use official APIs when available instead of scraping
  • +Identify your bot with descriptive user agent
  • +Cache results to minimize repeated requests
  • +Handle errors gracefully with retries and fallbacks
  • +Validate extracted data for accuracy

✗ Don't

  • −Don't scrape sites that explicitly forbid it (robots.txt, ToS)
  • −Don't overwhelm servers with rapid requests—use rate limiting
  • −Don't scrape personal data without consent and legal basis
  • −Don't ignore copyright on extracted content
  • −Don't assume HTML structure is stable—handle changes
  • −Don't use scraped data for commercial purposes without permission

💡 Pro Tips

  • ★Use CSS selectors or XPath for robust data extraction
  • ★Set up monitoring alerts for extraction failures (structure changed)
  • ★Implement exponential backoff for retries on failures
  • ★Store raw HTML for reprocessing if extraction logic changes
  • ★Combine with data analysis tools for insights from extracted data
  • ★Consider using official APIs or RSS feeds as more stable alternatives

Technical Details▌

Architecture

MCP server handles HTTP requests, HTML parsing, JavaScript rendering (if headless browser), and returns structured data to Claude.

Protocols

  • HTTP/HTTPS
  • WebSocket (for real-time sites)
  • Puppeteer/Playwright (for JavaScript sites)

Compatibility

  • Static HTML sites
  • JavaScript-rendered SPAs (with headless browser)
  • REST APIs
  • GraphQL endpoints

When to Use This▌

✓ 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.

Integration▌

  • →Scheduled monitoring with change detection
  • →Multi-source data aggregation pipelines
  • →Fallback to web scraping when API rate limits hit
  • →Headless browser for JavaScript-heavy sites

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.8★★★★★54 reviews
  • ★★★★★Shikha Mishra· Dec 28, 2024

    We evaluated Fetch (Web Content & YouTube Transcripts) against two servers with overlapping tools; this profile had the clearer scope statement.

  • ★★★★★Ganesh Mohane· Dec 20, 2024

    Fetch (Web Content & YouTube Transcripts) reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • ★★★★★Chen Agarwal· Dec 16, 2024

    Fetch (Web Content & YouTube Transcripts) has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • ★★★★★Isabella Torres· Dec 4, 2024

    We wired Fetch (Web Content & YouTube Transcripts) into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • ★★★★★Amina Martin· Dec 4, 2024

    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.

  • ★★★★★Nia Martin· Nov 23, 2024

    According to our notes, Fetch (Web Content & YouTube Transcripts) benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • ★★★★★Tariq Perez· Nov 23, 2024

    Fetch (Web Content & YouTube Transcripts) has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • ★★★★★Sakshi Patil· Nov 11, 2024

    I recommend Fetch (Web Content & YouTube Transcripts) for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • ★★★★★Nia Thompson· Nov 7, 2024

    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.

  • ★★★★★Isabella Rao· Oct 26, 2024

    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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