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Understanding Story Data Structure and Fields
What is Story Data in Hacker News?
When you interact with the Hacker News MCP Server, stories are the fundamental content type you'll work with most frequently. Each story represents a submission to Hacker News—whether it's a link to an external article, a "Show HN" project, an "Ask HN" question, or a job posting. Understanding how story data is structured helps you extract exactly the information you need and interpret the results accurately.
Core Story Fields
Every story retrieved through the server contains a consistent set of fields that describe its properties and current status on the platform.
Identification and Content
The id field provides a unique numeric identifier for each story, which you can use to reference specific submissions or retrieve their comment threads. The title contains the headline as submitted by the author, while the url field points to the external resource being discussed (when applicable—text posts may not have URLs).
Author and Timing
The by field indicates the username of the person who submitted the story. Combined with the time field, which contains a Unix timestamp of when the submission was posted, you can track who's sharing content and understand the recency of discussions.
Community Engagement
The score field represents the number of upvotes a story has received, indicating community interest and approval. Higher scores typically correlate with greater visibility on the site. The descendants field tells you the total number of comments in the discussion, helping you gauge how much conversation a story has generated.
Story Types
The type field will show "story" for standard submissions, though you may encounter other types like "job" or "poll" when browsing different sections of Hacker News.
Working with Story Collections
When you request feeds like "top stories" or "new stories," the server returns lists of story IDs rather than complete story objects. This approach mirrors how Hacker News structures its API and allows for efficient data retrieval. You can then request full details for specific stories that interest you.
Practical Applications
Understanding these fields enables sophisticated filtering and analysis. You might track stories with high scores but few comments to find widely-appreciated content that hasn't sparked debate, or monitor new submissions from specific authors to follow particular contributors' activity.
The structured nature of story data makes it straightforward to build custom workflows—whether you're aggregating daily top stories, tracking discussions about specific technologies, or analyzing submission patterns over time.
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