search-web

Web Fetch

kwp-lab

by kwp-lab

Web Fetch is a web scraping tool that converts web pages to markdown, extracts images, and works with proxies for secure

Fetches and converts web pages to markdown format with automatic image extraction and proxy support for accessing content through corporate networks or restricted environments.

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

Built-in proxy supportAutomatic image extractionZero setup with npx

best for

  • / Corporate environments with proxy requirements
  • / Content research and web scraping
  • / Converting web articles for analysis

capabilities

  • / Fetch web pages and convert to markdown
  • / Extract image URLs from web content
  • / Route requests through HTTP/HTTPS proxies
  • / Access content through corporate firewalls

what it does

Fetches web pages and converts them to markdown format while extracting image URLs. Includes proxy support for corporate networks and restricted environments.

about

Web Fetch is a community-built MCP server published by kwp-lab that provides AI assistants with tools and capabilities via the Model Context Protocol. Web Fetch is a web scraping tool that converts web pages to markdown, extracts images, and works with proxies for secure It is categorized under search web.

how to install

You can install Web Fetch 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

Web Fetch is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

MCP Fetch

Model Context Protocol server for fetching web content with custom http proxy. This allows Claude Desktop (or any MCP client) to fetch web content and handle images appropriately.

<a href="https://glama.ai/mcp/servers/@kwp-lab/mcp-fetch"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@kwp-lab/mcp-fetch/badge" /> </a>

This repository forks from the @smithery/mcp-fetch and replaces the node-fetch implementation with the library node-fetch-native.

The server will use the http_proxy and https_proxy environment variables to route requests through the proxy server by default if they are set. You also can set the MCP_HTTP_PROXY environment variable to use a different proxy server.

Available Tools

  • fetch: Retrieves URLs from the Internet and extracts their content as markdown. If images are found, their URLs will be included in the response.

Image Processing Specifications:

Only extract image urls from the article content, and append them to the tool result:

{
  "params": {
    "url": "https://www.example.com/articles/123"
  },
  "response": {
    "content": [
      {
        "type": "text",
        "text": "Contents of https://www.example.com/articles/123:
Here is the article content

Images found in article:
- https://www.example.com/1.jpg.webp
- https://www.example.com/2.jpg.webp
- https://www.example.com/3.webp"
      }
    ]
  }
}

Quick Start (For Users)

To use this tool with Claude Desktop, simply add the following to your Claude Desktop configuration (~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "tools": {
    "fetch": {
      "command": "npx",
      "args": ["-y", "@kwp-lab/mcp-fetch"],
      "env": {
        "MCP_HTTP_PROXY": "https://example.com:10890" // Optional, remove if not needed
      }
    }
  }
}

This will automatically download and run the latest version of the tool when needed.

Required Setup

  1. Enable Accessibility for Claude:
    • Open System Settings
    • Go to Privacy & Security > Accessibility
    • Click the "+" button
    • Add Claude from your Applications folder
    • Turn ON the toggle for Claude

For Developers

The following sections are for those who want to develop or modify the tool.

Prerequisites

Installation

Installing via Smithery

To install MCP Fetch for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @kwp-lab/mcp-fetch --client claude

Manual Installation

git clone https://github.com/kwp-lab/mcp-fetch.git
cd mcp-fetch
npm install
npm run build

Configuration

  1. Make sure Claude Desktop is installed and running.

  2. Install tsx globally if you haven't:

    npm install -g tsx
    # or
    pnpm add -g tsx
    
  3. Modify your Claude Desktop config located at:

~/Library/Application Support/Claude/claude_desktop_config.json

You can easily find this through the Claude Desktop menu:

  1. Open Claude Desktop
  2. Click Claude on the Mac menu bar
  3. Click "Settings"
  4. Click "Developer"

Add the following to your MCP client's configuration:

{
  "tools": {
    "fetch": {
      "args": ["tsx", "/path/to/mcp-fetch/index.ts"]
    }
  }
}

FAQ

What is the Web Fetch MCP server?
Web Fetch 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 Web Fetch?
This profile displays 54 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 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

4.654 reviews
  • Aditi Wang· Dec 12, 2024

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

  • Aditi Li· Dec 4, 2024

    Web Fetch reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Hana Desai· Nov 23, 2024

    I recommend Web Fetch for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Yash Thakker· Nov 15, 2024

    Web Fetch is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Aanya Jackson· Nov 3, 2024

    According to our notes, Web Fetch benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Aanya Park· Oct 22, 2024

    Web Fetch has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Hana Thompson· Oct 14, 2024

    Strong directory entry: Web Fetch surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Dhruvi Jain· Oct 6, 2024

    We evaluated Web Fetch against two servers with overlapping tools; this profile had the clearer scope statement.

  • Min Johnson· Sep 25, 2024

    According to our notes, Web Fetch benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Kwame Chen· Sep 25, 2024

    Web Fetch is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

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