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.
Give Claude and any AI agent real-world access
Pass a raw XML feed string and receive a clean JSON array containing titles, links, dates, and content for multiple items.
Processes both RSS 2.0 and Atom formats using the same unified structure.
Identifies audio or video enclosures within a feed, providing URLs, durations, and file sizes.
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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.
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Start using RSS Feed Parser MCPParse Rss Feed
Converts raw RSS 2.0 or Atom XML strings into structured JSON, extracting titles, links, dates, categories, and full content snippets.
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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.
019e38e6-a2af-72af-915b-c6180315afff How to set up RSS Feed Parser MCP
The bottom line is that you trade unpredictable website code for predictable, standardized data objects.
You supply the raw XML string from the RSS or Atom feed.
The MCP processes this stream, extracting all metadata (titles, links, dates, content) into a structured JSON format.
Your agent receives the clean JSON object, which is ready for immediate use in workflows like summarization or data storage.
Who uses RSS Feed Parser MCP
Content strategists, SEO analysts, and technical product managers use this MCP. They struggle with the manual labor of aggregating content from dozens of external sources daily. The pain point is time—spending hours cleaning up scraped HTML instead of analyzing trends.
Uses it to automatically collect and analyze articles from competitor blogs, ensuring the agent always has the most current content streams for trend spotting.
Connects feeds to pull publication dates and category tags across multiple sites, helping map out comprehensive topic coverage gaps in the market.
Uses it to validate if external data sources (like news aggregators) provide consistent metadata fields before building a new internal reporting dashboard.
Benefits of connecting RSS Feed Parser MCP
Stop dealing with inconsistent HTML. This MCP reads native feed XML/Atom and delivers structured JSON, so your agent never has to worry about broken tags or malformed code.
Process entire content streams, not just single articles. You can pass a raw feed string and get up to twenty items returned in one clean batch of data.
Capture rich podcast details automatically. The tool extracts enclosure URLs, durations, and file sizes from episode feeds, which is critical for media monitoring.
Centralize multiple formats. It treats RSS 2.0 and Atom feeds the same way, unifying disparate content sources into a single, predictable JSON structure.
Eliminate manual data entry. Instead of copying titles, links, and dates across dozens of tabs, your agent gets all that metadata in one go.
RSS Feed Parser MCP use cases
Monitoring Competitor News
A content strategist wants to track five competitors' latest posts. They use the MCP to feed the raw XML for each site, allowing their agent to consolidate titles and publication dates into a single JSON list for weekly reporting.
Building a Podcast Content Index
A marketing team needs all recent episode details (URL, duration, description) from a podcast. The MCP ingests the feed and gives them an array of clean objects containing the necessary enclosure data for their newsletter.
Curating Industry News Briefs
A researcher needs to summarize key takeaways from three industry news aggregators. They run the parse_rss_feed tool on all three feeds, receiving a consistent JSON output that can be fed into a summarization model.
Validating Content Source Integrity
A product team needs to ensure an external data partner's feed is reliable. They use the MCP to test various raw XML strings, verifying that all expected metadata fields—like author and category—are consistently present.
RSS Feed Parser MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Using generic web scrapers
Trying to scrape content directly using basic HTTP requests or a simple HTML parser. This fails when the target site changes its internal structure.
Pass the raw XML feed string and use parse_rss_feed. The MCP is designed specifically for standardized feed formats, making it immune to common website layout breaks.
Handling multiple feeds separately
Running separate scripts or workflows for RSS 2.0 feeds versus Atom feeds, leading to inconsistent output handling.
The MCP unifies both RSS 2.0 and Atom formats into the same JSON structure. You just feed it the source; you get one standardized result.
When to use RSS Feed Parser MCP
Use this MCP if your primary need is to gather structured metadata (titles, links, dates) from multiple content sources that publish via a standard feed format. If you're building a system that consumes information from blogs, news aggregators, or podcasts, this is exactly what you want. You must have the raw XML or Atom URL ready for input.
Don't use this if you are dealing with proprietary data endpoints that don't offer an RSS feed, or if your content sources require login credentials to access. For those cases, a specialized API connector would be better. This MCP focuses purely on transforming standard, publicly available feed XML.
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.