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Every piece of content on Hacker News—whether it's a story, comment, poll, or job posting—has a unique numerical identifier called an item ID. These IDs are assigned sequentially as content is created, and they serve as the primary way to retrieve specific content directly through the Hacker News MCP Server.
Querying by item ID is essential when you need to access specific content that you've already identified. Perhaps you're following up on a particular discussion, analyzing a specific story over time, or retrieving content referenced elsewhere. Unlike browsing feeds that show curated lists, ID-based queries give you direct, precise access to exactly what you need.
To retrieve a specific item, you simply need its numerical ID. You can request content through natural language queries to your AI assistant. For example:
The server will fetch the complete information about that item, including its type (story, comment, poll, etc.), title (if applicable), text content, author, timestamp, score, and any associated metadata.
Item IDs appear in several places throughout Hacker News:
item?id=37845290
When you query an item by ID, the server returns structured data that varies based on the item type:
For stories: You'll receive the title, URL (if it's a link post), submission time, author username, current score, and the number of comments.
For comments: The response includes the comment text, author, timestamp, and references to parent items, allowing you to understand the comment's context within a discussion thread.
For polls: You'll get the poll question along with its associated poll options and voting data.
Direct ID queries are particularly useful for monitoring specific stories over time to track how scores and comment counts change, retrieving full comment trees by starting with a root comment ID, or building references to specific discussions in your own documentation or analysis.
This straightforward querying mechanism ensures you always have direct access to any Hacker News content, making it easy to build sophisticated workflows around specific items of interest.
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