search-web

RSS Feed Parser

veithly

by veithly

RSS Feed Parser is a powerful rss feed generator and rss link generator with RSSHub integration, perfect for creating cu

Provides RSS feed parsing and retrieval with RSSHub integration, automatically trying multiple instances when one fails and supporting custom rsshub:// protocol URLs for accessing current content from websites, social platforms, and news sources that don't natively provide RSS feeds.

github stars

30

0 commentsdiscussion

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

Multi-instance failover supportWorks with sites that lack native RSSClean text extraction

best for

  • / Content aggregation from multiple sources
  • / Monitoring news sites and social media
  • / Building custom RSS readers
  • / Extracting structured data from websites without native feeds

capabilities

  • / Parse standard RSS and Atom feeds
  • / Access RSSHub feeds with rsshub:// URLs
  • / Retrieve content from social platforms via RSSHub
  • / Extract clean text from feed content
  • / Specify custom item count limits
  • / Auto-retry failed requests across multiple instances

what it does

Fetches and parses RSS/Atom feeds from any URL, with special support for RSSHub to create feeds from websites that don't natively offer them.

about

RSS Feed Parser is a community-built MCP server published by veithly that provides AI assistants with tools and capabilities via the Model Context Protocol. RSS Feed Parser is a powerful rss feed generator and rss link generator with RSSHub integration, perfect for creating cu It is categorized under search web.

how to install

You can install RSS Feed Parser 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

Apache-2.0

RSS Feed Parser is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

RSS MCP Server

NPM Version

This is a Model Context Protocol (MCP) server built with TypeScript. It provides a versatile tool to fetch and parse any standard RSS/Atom feed, and also includes special support for RSSHub feeds. With this server, language models or other MCP clients can easily retrieve structured content from various web sources.

<a href="https://glama.ai/mcp/servers/@veithly/rss-mcp"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@veithly/rss-mcp/badge" alt="RSS Server MCP server" /> </a>

The server comes with a built-in list of public RSSHub instances and supports a polling mechanism to automatically select an available instance, significantly improving the success rate and stability of data retrieval.

✨ Features

  • Universal Feed Parsing: Fetch and parse any standard RSS/Atom feed from a given URL.
  • Enhanced RSSHub Support: Provides a tool named get_feed to fetch any RSSHub-supported feed via MCP, with multi-instance support.
  • Customizable Item Count: Specify the number of feed items to retrieve, with support for fetching all items.
  • Multi-instance Support: Includes a list of public RSSHub instances and automatically polls to find an available service.
  • Smart URL Parsing: Supports standard RSSHub URLs and a simplified rsshub:// protocol format.
  • Priority Instance Configuration: Allows setting a preferred RSSHub instance via the PRIORITY_RSSHUB_INSTANCE environment variable.
  • Robust Error Handling: If a request to one instance fails, it automatically tries the next one until it succeeds or all instances have failed.
  • Content Cleaning: Uses Cheerio to clean the feed content and extract plain text descriptions.
  • Standardized Output: Converts the fetched RSS feed into a structured JSON format.

📦 Installation

First, clone the project repository, then install the required dependencies.

git clone https://github.com/veithly/rss-mcp.git
cd rss-mcp
npm install

🚀 Usage

1. Build the Project

Before running, you need to compile the TypeScript code into JavaScript:

npm run build

2. Run the Server

After a successful build, start the MCP server:

npm start

The server will then communicate with the parent process (e.g., Cursor) via Stdio.

3. Configure a Priority Instance (Optional)

You can create a .env file to specify a priority RSSHub instance. This is very useful for users who have a private, stable instance.

Create a .env file in the project root directory and add the following content:

PRIORITY_RSSHUB_INSTANCE=https://my-rsshub.example.com

The server will automatically load this configuration on startup and place it at the top of the polling list.

🔧 MCP Server Configuration

To use this server with an MCP client like Cursor, you need to add it to your configuration file.

Method 1: Using npx (Recommended)

This package is published on npm, so you can use npx to run the server without a local installation. This is the easiest method.

  1. Direct Invocation: You can run the server directly from your terminal using npx:

    npx rss-mcp
    
  2. MCP Client Configuration: To integrate with an MCP client like Cursor, add the following to your configuration file (e.g., ~/.cursor/mcp_settings.json):

    {
      "name": "rss",
      "command": ["npx", "rss-mcp"],
      "type": "stdio"
    }
    

Method 2: Local Installation

If you have cloned the repository locally, you can run it directly with node.

  1. Clone and build the project as described in the "Installation" and "Usage" sections.

  2. Locate your MCP configuration file.

  3. Add the following server entry, making sure to use the absolute path to the compiled index.js file:

    {
      "name": "rss",
      "command": ["node", "/path/to/your/rss-mcp/dist/index.js"],
      "type": "stdio"
    }
    

    Important: Replace /path/to/your/rss-mcp/dist/index.js with the correct absolute path on your system.

After adding the configuration, restart your MCP client (e.g., Cursor) for the changes to take effect. The rss server will then be available, and you can call the get_feed tool.

🛠️ Tool Definition

get_feed

Fetches and parses an RSS feed from a given URL. It supports both standard RSS/Atom feeds and RSSHub feeds.

Input Parameters

  • url (string, required): The URL of the RSS feed to fetch. Two formats are supported:
    1. Standard URL: https://rsshub.app/bilibili/user/dynamic/208259
    2. rsshub:// protocol: rsshub://bilibili/user/dynamic/208259 (the server will automatically match an available instance)
  • count (number, optional): The number of RSS feed items to retrieve.
    • Default: 1
    • Retrieve all: 0

Output

Returns a JSON string containing the feed information, with the following structure:

{
  "title": "bilibili User Dynamics",
  "link": "https://space.bilibili.com/208259",
  "description": "bilibili User Dynamics",
  "items": [
    {
      "title": "[Dynamic Title]",
      "description": "Plain text content of the dynamic...",
      "link": "https://t.bilibili.com/1234567890",
      "guid": "https://t.bilibili.com/1234567890",
      "pubDate": "2024-05-20T12:30:00.000Z",
      "author": "Author Name",
      "category": ["Category1", "Category2"]
    }
  ]
}

📜 Main Dependencies

📄 License

This project is licensed under the Apache-2.0 License.

FAQ

What is the RSS Feed Parser MCP server?
RSS Feed Parser 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 RSS Feed Parser?
This profile displays 45 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.

List & Promote Your MCP Server

Share your MCP server with the developer community

GET_STARTED →
MCP server reviews

Ratings

4.645 reviews
  • Ama Sanchez· Dec 28, 2024

    We evaluated RSS Feed Parser against two servers with overlapping tools; this profile had the clearer scope statement.

  • Advait Anderson· Dec 8, 2024

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

  • Rahul Santra· Nov 27, 2024

    I recommend RSS Feed Parser for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Advait Singh· Nov 27, 2024

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

  • Chinedu Gupta· Nov 19, 2024

    Useful MCP listing: RSS Feed Parser is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Pratham Ware· Oct 18, 2024

    Strong directory entry: RSS Feed Parser surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Emma Garcia· Oct 18, 2024

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

  • Anaya Menon· Oct 10, 2024

    RSS Feed Parser reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Advait White· Sep 17, 2024

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

  • Anaya Mehta· Sep 9, 2024

    Strong directory entry: RSS Feed Parser surfaces stars and publisher context so we could sanity-check maintenance before adopting.

showing 1-10 of 45

1 / 5