ZenFeed MCP Server

ZenFeed is an MCP server that transforms the raw, static nature of RSS feeds into a dynamic, AI‑enhanced content hub. In an era where information overload is the norm, ZenFeed tackles the problem of sifting through endless articles by providing personalized recommendations and real‑time alerts. Developers can deploy their own instance to maintain full control over data, privacy, and integration with existing workflows.

At its core, ZenFeed pulls new entries from any standard RSS source, normalizes the content, and feeds it into a machine‑learning pipeline that scores relevance against user interests. The server exposes these enriched items through MCP resources, allowing AI assistants to query for the most pertinent articles or summaries on demand. This makes it trivial to build chatbots that can answer questions like “What’s the latest on quantum computing?” or “Show me top stories from TechCrunch that match my interests.” The AI‑powered recommendation engine is a standout feature: it learns from user interactions, refines its suggestions, and can even surface related content across multiple feeds.

Key capabilities include real‑time monitoring of feed changes, email alert generation with concise highlights, and integration points for Prometheus to track health metrics. Developers can leverage the OpenAI API through ZenFeed’s built‑in connector, enabling richer natural language processing and summarization without handling the heavy lifting themselves. The customizable dashboard gives users a visual interface to manage feeds, adjust preferences, and review analytics—all while the MCP server keeps the data accessible for programmatic consumption.

ZenFeed shines in scenarios such as research assistants that need to stay current on niche topics, news aggregators for enterprises that want tailored content streams, or personal knowledge bases where users can ingest and query daily updates. By exposing its functionality via MCP, the server fits seamlessly into AI workflows: a Claude assistant can call a “fetchFeed” tool to retrieve the latest articles, then pass them through a summarization prompt before presenting them to the user. The server’s modular architecture also allows teams to extend or replace components—such as swapping out the recommendation model—for specialized use cases.

In summary, ZenFeed turns ordinary RSS feeds into a smart, user‑centric knowledge source. Its combination of AI recommendation, real‑time monitoring, and MCP integration gives developers a powerful platform to build conversational agents that can deliver up‑to‑date, personalized content with minimal effort.