Fetch and Convert▌
by tokenizin-agency
Fetch and Convert turns web content into Markdown using JSDOM and Turndown—perfect for link markdown and md format needs
Fetches and converts web content to Markdown using JSDOM and Turndown.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Content creators extracting articles for research
- / Developers scraping web data for applications
- / Documentation teams converting web content to Markdown
- / Data analysts gathering information from websites
capabilities
- / Fetch web pages as raw HTML
- / Convert web content to clean Markdown
- / Extract plain text from web pages
- / Retrieve and parse JSON from URLs
- / Add custom headers for authenticated requests
what it does
Fetches web content from any URL and converts it into different formats like HTML, Markdown, plain text, or JSON. Built with JSDOM and Turndown for reliable content transformation.
about
Fetch and Convert is a community-built MCP server published by tokenizin-agency that provides AI assistants with tools and capabilities via the Model Context Protocol. Fetch and Convert turns web content into Markdown using JSDOM and Turndown—perfect for link markdown and md format needs It is categorized under search web, developer tools. This server exposes 4 tools that AI clients can invoke during conversations and coding sessions.
how to install
You can install Fetch and Convert 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. This server supports remote connections over HTTP, so no local installation is required.
license
MIT
Fetch and Convert 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 NPX Fetch
<div align="center">A powerful MCP server for fetching and transforming web content into various formats (HTML, JSON, Markdown, Plain Text) with ease.
Installation • Features • Usage • Documentation • Contributing
</div><a href="https://glama.ai/mcp/servers/m2a0ue08n2"><img width="380" height="200" src="https://glama.ai/mcp/servers/m2a0ue08n2/badge" alt="NPX Fetch MCP server" /></a>
🚀 Features
- 🌐 Universal Content Fetching: Supports HTML, JSON, plain text, and Markdown formats
- 🔒 Custom Headers Support: Add authentication and custom headers to your requests
- 🛠 Built-in Transformations: Automatic conversion between formats
- ⚡ High Performance: Built with modern JavaScript features and optimized for speed
- 🔌 MCP Compatible: Seamlessly integrates with Claude Desktop and other MCP clients
- 🎯 Type-Safe: Written in TypeScript with full type definitions
📦 Installation
NPM Global Installation
npm install -g @tokenizin/mcp-npx-fetch
Direct Usage with NPX
npx @tokenizin/mcp-npx-fetch
📚 Documentation
Available Tools
fetch_html
Fetches and returns raw HTML content from any URL.
{
url: string; // Required: Target URL
headers?: { // Optional: Custom request headers
[key: string]: string;
};
}
fetch_json
Fetches and parses JSON data from any URL.
{
url: string; // Required: Target URL
headers?: { // Optional: Custom request headers
[key: string]: string;
};
}
fetch_txt
Fetches and returns clean plain text content, removing HTML tags and scripts.
{
url: string; // Required: Target URL
headers?: { // Optional: Custom request headers
[key: string]: string;
};
}
fetch_markdown
Fetches content and converts it to well-formatted Markdown.
{
url: string; // Required: Target URL
headers?: { // Optional: Custom request headers
[key: string]: string;
};
}
🔧 Usage
CLI Usage
Start the MCP server directly:
mcp-npx-fetch
Or via npx:
npx @tokenizin/mcp-npx-fetch
Claude Desktop Integration
-
Locate your Claude Desktop configuration file:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%/Claude/claude_desktop_config.json - Linux:
~/.config/Claude/claude_desktop_config.json
- macOS:
-
Add the following configuration to your
mcpServersobject:
{
"mcpServers": {
"fetch": {
"command": "npx",
"args": ["-y", "@tokenizin/mcp-npx-fetch"],
"env": {}
}
}
}
💻 Local Development
- Clone the repository:
git clone https://github.com/tokenizin-agency/mcp-npx-fetch.git
cd mcp-npx-fetch
- Install dependencies:
npm install
- Start development mode:
npm run dev
- Run tests:
npm test
🛠 Technical Stack
- Model Context Protocol SDK - Core MCP functionality
- JSDOM - HTML parsing and manipulation
- Turndown - HTML to Markdown conversion
- TypeScript - Type safety and modern JavaScript features
- Zod - Runtime type validation
🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.
- Fork the repository
- Create your feature branch (
git checkout -b feature/AmazingFeature) - Commit your changes (
git commit -m 'Add some AmazingFeature') - Push to the branch (
git push origin feature/AmazingFeature) - Open a Pull Request
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
<div align="center"> Made with ❤️ by <a href="https://github.com/tokenizin-agency">PT Tokenizin Technology Agency</a> </div>
FAQ
- What is the Fetch and Convert MCP server?
- Fetch and Convert 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 and Convert?
- This profile displays 61 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 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.Install web automation MCP server via npm or pip
- 2.Configure allowed domains and rate limits in MCP config
- 3.Test with simple fetch: 'Get content from example.com'
- 4.Progress to extraction: 'Extract all product prices from this page'
- 5.Set up monitoring: 'Check this URL daily for changes'
- 6.Parse structured data: 'Create CSV from this table'
- 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
4.7★★★★★61 reviews- ★★★★★Kabir Kim· Dec 24, 2024
We evaluated Fetch and Convert against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Zaid Sethi· Dec 20, 2024
According to our notes, Fetch and Convert benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Henry Verma· Dec 16, 2024
Useful MCP listing: Fetch and Convert is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Liam Park· Dec 8, 2024
Fetch and Convert is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Zaid Reddy· Nov 27, 2024
Fetch and Convert is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Rahul Santra· Nov 19, 2024
We evaluated Fetch and Convert against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Olivia White· Nov 11, 2024
Fetch and Convert has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Layla Choi· Nov 11, 2024
We evaluated Fetch and Convert against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Ishan Bhatia· Nov 7, 2024
Fetch and Convert reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Nikhil Farah· Nov 7, 2024
I recommend Fetch and Convert for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
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