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The Hacker News MCP Server provides multiple tools for retrieving story feeds and individual story data. This guide walks you through the available options for accessing different types of stories, from trending front-page content to the latest submissions.
Hacker News organizes content into several distinct feeds, each serving a different purpose:
Top Stories represent the most popular content currently on the front page, ranked by a combination of votes, time, and engagement. These stories have gained significant community traction and typically represent what the tech community is actively discussing.
New Stories shows the most recent submissions in chronological order, regardless of votes or engagement. This feed is ideal for discovering fresh content before it gains wider attention or monitoring emerging topics in real-time.
Best Stories highlights submissions that have demonstrated sustained value and quality based on community engagement patterns. This feed applies more sophisticated ranking than simple voting, identifying content with lasting impact.
To access any story feed, simply make a natural language request through your AI assistant. For example:
The server will return a structured list containing each story's key details: title, URL (if external), score, submission time, author, and the number of comments. This data arrives ready for analysis, summarization, or further exploration.
Once you've identified stories of interest from a feed, you can retrieve detailed information about specific submissions using their unique story ID. This provides access to the complete story metadata and serves as a starting point for exploring associated comments.
Simply reference a story by its ID or ask follow-up questions about stories you've already retrieved: "Tell me more about that story" or "Get details for story 35892314."
When monitoring trends, start with top stories to understand current community focus. For time-sensitive monitoring or content discovery, new stories provide the earliest signal. Use best stories when researching topics that benefit from community validation over time.
Feed data is retrieved in real-time, so repeated requests reflect current community activity. This makes the server suitable for both one-time research and ongoing monitoring scenarios.
The Tavily integration lets you perform AI-powered web searches and retrieve real-time information from across the internet directly within your MCP-enabled applications, enabling your AI assistants to access current data and factual content for more accurate and up-to-date responses.
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