Feed‑MCP: Bringing RSS Feeds Into Claude Desktop

Feed‑MCP is a Model Context Protocol (MCP) server that turns any RSS, Atom, or JSON feed into an interactive data source for Claude Desktop. By exposing feeds as MCP resources, the server allows AI assistants to query, summarize, and filter content in real time without leaving the chat interface. This bridges the gap between static web feeds and dynamic conversational AI, enabling developers to build richer, up‑to‑date knowledge bases directly within their workflows.

The server solves the problem of scattered information sources. Traditional RSS readers require a separate application or browser tab, making it cumbersome to retrieve the latest headlines while drafting a report or answering a question. Feed‑MCP eliminates that friction by embedding feed data into the MCP ecosystem, where Claude can treat each article as a structured record. Developers can therefore ask high‑level questions—such as “What are today’s top AI headlines?”—and receive concise, context‑aware responses that reflect the freshest content from multiple publishers.

Key capabilities include:

• Dynamic feed ingestion: The server accepts any number of URLs, pulling the latest items on each request. It supports common formats (RSS 2.0, Atom, JSON‑Feed) and automatically normalizes fields like title, link, author, and publication date.
• Rich query language: Claude can filter articles by keyword, date range, or source, and request summaries of multiple items in a single prompt. The MCP interface exposes these filters as parameters, keeping the conversational syntax natural.
• Batch summarization: Users can ask for a summary of the top N articles, and Feed‑MCP returns concise overviews that can be used for quick scans or deeper research.
• OPML integration: Existing feed collections from Feedly, Inoreader, or other readers can be exported as OPML and fed into the server, preserving user preferences without manual re‑entry.

Real‑world scenarios that benefit from Feed‑MCP include:

• Research assistants: A scientist can query the latest papers or blog posts in their field, getting summaries before deciding which to read in full.
• Content creators: Journalists or marketers can stay on top of industry trends, pulling headline lists or thematic summaries into their drafting process.
• Product managers: By querying feeds from competitors’ blogs or tech news sites, teams can quickly gauge market sentiment and emerging features.
• Podcast producers: The server can aggregate episode listings, enabling quick checks for new releases or topic coverage across multiple shows.

Integration into AI workflows is straightforward. Once the MCP server is registered in Claude Desktop’s configuration, any prompt that references the feed‑mcp resource automatically triggers a network request to fetch current items. The returned data is then incorporated into the conversation context, allowing Claude to generate responses that are both timely and tailored to the user’s interests. Because MCP is stateless, each query pulls fresh data, ensuring that the assistant never relies on stale cached information.

Unique advantages of Feed‑MCP lie in its simplicity and extensibility. It requires no custom API keys or authentication for public feeds, making it immediately usable out of the box. Its Docker‑based deployment means developers can run it locally or in a CI environment without complex setup, and the server’s lightweight Go implementation guarantees low latency. For teams looking to embed real‑time news, blogs, or podcasts into AI‑driven tools, Feed‑MCP provides a plug‑and‑play solution that turns static web feeds into dynamic conversational knowledge.