Vinkius

RSS Feed Parser MCP. Turns messy feeds into clean, usable data.

The RSS Feed Parser takes raw XML or Atom feed data from any blog, news site, or podcast and converts it into clean, structured JSON objects. It extracts all critical metadata—titles, links, publication dates, authors, categories, and full content snippets—without needing to scrape messy HTML. This lets your agent process reliable, machine-readable content feeds instantly.

RSS Feed Parser MCP is compatible with Claude Claude
RSS Feed Parser MCP is compatible with ChatGPT ChatGPT
RSS Feed Parser MCP is compatible with Cursor Cursor
RSS Feed Parser MCP is compatible with Gemini Gemini
RSS Feed Parser MCP is compatible with Windsurf Windsurf
RSS Feed Parser MCP is compatible with VS Code VS Code
RSS Feed Parser MCP is compatible with JetBrains JetBrains
RSS Feed Parser MCP is compatible with Vercel Vercel
See Vinkius in Action

Give Claude and any AI agent real-world access

Extract structured article data

Pass a raw XML feed string and receive a clean JSON array containing titles, links, dates, and content for multiple items.

Handle multiple feed standards

Processes both RSS 2.0 and Atom formats using the same unified structure.

Extract podcast metadata

Identifies audio or video enclosures within a feed, providing URLs, durations, and file sizes.

Waiting for input…

AI Agent
RSS Feed Parser

What AI agents can do with RSS Feed Parser: 1 Tool Available

Use the single available tool to convert raw XML feed streams into standardized JSON data objects ready for immediate AI processing.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using RSS Feed Parser MCP

Parse Rss Feed

Converts raw RSS 2.0 or Atom XML strings into structured JSON, extracting titles, links, dates, categories, and full content snippets.

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

RSS Feed Parser MCP is compatible with Claude

Claude AI

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

3

Start a conversation

Open a new chat. The RSS Feed Parser integration is available immediately — no restart needed.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

  • Import from OpenAPI, Swagger, or YAML specs
  • Create Agent Skills with progressive disclosure
  • Deploy to edge with MCPFusion framework
  • Built in DLP, auth, and compliance on each call
  • Real time usage dashboard and cost metering
  • Publish to catalog or keep private
Start building

Make Your AI Do More

Start with RSS Feed Parser, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.

  • Use this MCP plus 5,200+ others, all in one place
  • Add new capabilities to your AI anytime you want
  • Connections are secured and governed automatically
  • Track usage and costs across all your servers
  • Works with Claude, ChatGPT, Cursor, and more
  • New servers added to the catalog weekly
RSS Feed Parser MCP server cover

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by rss-parser. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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The Daily Pain of Content Aggregation

Think about what it takes today: you have to open one browser tab for the tech news, another for the industry blog, and a third for the competitor's site. Then, for every single article, you manually copy the title, paste the link into your spreadsheet, and then click through to get the publication date. If you need to do this across twenty sources, it takes hours of repetitive clicking and copy-pasting.

With this MCP, that entire process vanishes. You feed the raw XML string—the source material itself—into your agent using `parse_rss_feed`. What comes back isn't a spreadsheet; it’s clean JSON containing every title, link, date, author, and content snippet you need, ready to be indexed or summarized automatically.

Parsing Feeds with the RSS Feed Parser

The manual steps that go away are: opening multiple browser tabs, navigating to different article pages, and manually extracting metadata one item at a time. You no longer have to worry about whether the source site changed its HTML structure or if you missed an enclosure URL.

Now, feeding data is a single step. You send the feed XML, and you get reliable, structured JSON back. It’s predictable, standardized content for your agent.

What RSS Feed Parser MCP does for your AI

Content teams spend way too much time manually copying article data from multiple sources. You're supposed to monitor twenty competitor blogs and five industry news sites, but you end up staring at fragmented HTML that breaks every other day.

This MCP changes that. It reads native web feeds—the XML or Atom format—and turns the entire stream into clean JSON objects. This means your agent gets predictable data: titles, links, publication dates, authors, and full content snippets, all packaged neatly for summarization or automated distribution. You don't have to worry about messy DOM traversal; this tool handles the tough parsing work so you can focus on what matters.

Whether it’s an entire blog feed or a podcast channel with enclosures, the data is structured and ready to go. Accessing reliable content feeds like this used to require custom scrapers for every single site. Now, through Vinkius, your agent gets access to one unified parser that handles both RSS 2.0 and Atom formats identically.

Built · Hosted · Managed by Vinkius RSS Feed Parser - Parse Content Feeds for Your AI Agent
Server ID 019e38e6-a2af-72af-915b-c6180315afff
Vinkius Inspector
Compliance Grade A+
Score 100/100
Vinkius Inspector Badge — Score 100/100

Frequently asked questions about RSS Feed Parser MCP

How do I use the RSS Feed Parser with podcast feeds? +

The MCP handles podcast data by extracting enclosure metadata. You simply pass the feed XML; it returns a structured JSON object that includes URLs, durations, and descriptions for every episode.

Does the RSS Feed Parser support Atom feeds or only RSS 2.0? +

No, the MCP is built to handle both. It parses both RSS 2.0 and Atom formats identically, unifying them into one consistent JSON structure for your agent.

What kind of data does parse_rss_feed extract? +

It extracts comprehensive metadata including the title, full link, publication date, author, categories, content snippet, and even podcast enclosure details into a single structured JSON object.

Can I use the RSS Feed Parser for news sites that require logins? +

No. This MCP requires access to the public feed XML/Atom URL. If the site content is paywalled or behind a login, you won't be able to parse it.

Is this better than simple web scraping? +

Yes. Traditional scraping parses messy HTML; this MCP understands standardized feed XML and delivers clean JSON directly. It’s reliable because the input format is controlled by the web standard, not the site's design.