by missionsquad
RSS feed server with intelligent caching, batch processing, content monitoring, and full‑text search for automated news
Fetches and manages RSS/Atom feeds with intelligent caching, batch processing, and content search. Helps monitor multiple news sources and extract feed content in various formats.
RSS is a community-built MCP server published by missionsquad that provides AI assistants with tools and capabilities via the Model Context Protocol. RSS feed server with intelligent caching, batch processing, content monitoring, and full‑text search for automated news It is categorized under developer tools, productivity. This server exposes 6 tools that AI clients can invoke during conversations and coding sessions.
You can install RSS 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.
Apache-2.0
RSS 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.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
RSS is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
I recommend RSS for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
We evaluated RSS against two servers with overlapping tools; this profile had the clearer scope statement.
RSS is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Useful MCP listing: RSS is the kind of server we cite when onboarding engineers to host + tool permissions.
Strong directory entry: RSS surfaces stars and publisher context so we could sanity-check maintenance before adopting.
RSS has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
We evaluated RSS against two servers with overlapping tools; this profile had the clearer scope statement.
I recommend RSS for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
RSS is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
showing 1-10 of 49
A Model Context Protocol (MCP) server for fetching, parsing, and managing RSS feeds.
yarn add @missionsquad/mcp-rss or npm install @missionsquad/mcp-rssyarn
.env.example to .env..env and set the necessary environment variables.yarn build
yarn start
fetch_rss_feed: Fetches and parses a single RSS feed.fetch_multiple_feeds: Fetches multiple RSS feeds in parallel or sequentially.monitor_feed_updates: Checks for new items in a feed since a specific time.search_feed_items: Searches for content across one or more RSS feeds.extract_feed_content: Extracts and formats content from feed items. Supports json, markdown, html, and text formats.get_feed_headlines: Gets a list of headlines from a feed. Supports json, markdown, html, and text formats.rss://cache/{feedUrl}: Access cached feed data.rss://opml/export: Export all monitored feeds in OPML format.Configure the server using environment variables defined in .env. See .env.example for all available options.
You can test the mcp-rss server and other MCP servers on the Mission Squad platform. Mission Squad is an Agentic AI Platform that allows you to build, manage, and deploy cooperative agents that connect to any model, leverage private data, and automate complex tasks. Sign up for a free account to get started
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.