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When you retrieve stories from Hacker News through the MCP server, each story comes with a set of structured data fields that provide detailed information about the submission. Understanding these fields helps you make sense of the data you receive and enables you to extract the most relevant information for your needs.
Every Hacker News story includes several core fields that describe its content and community engagement. These typically include the story's unique identifier (ID), the title of the submission, and the URL it links to (if it's a link submission rather than a text post). You'll also find the author's username, which tells you who submitted the story to the platform.
Stories include engagement data that reveals how the community has responded to the submission. The score field indicates the number of upvotes the story has received, providing a quick measure of community interest and approval. Higher scores generally indicate content that resonates with the Hacker News audience.
You'll also see the number of comments (descendants) associated with each story. This metric shows how much discussion the submission has generated, which can be just as valuable as the vote count. Some stories may have moderate scores but extensive, high-quality discussions in the comments.
Time-related fields help you understand when content was published and how current it is. The time
field contains a timestamp indicating when the story was submitted to Hacker News. This information is crucial for tracking trends, understanding the age of discussions, or filtering content by recency.
When monitoring trending topics or analyzing community response over time, these timestamps become essential reference points for contextualizing the data.
Stories come in different types, including standard links, "Ask HN" questions where users seek community input, "Show HN" posts where people showcase their projects, and job postings. Understanding the type helps you categorize content and respond appropriately to different submission formats.
Some stories may also have states indicating whether they've been flagged by moderators or marked as dead, which affects their visibility on the site.
These data fields work together to give you a complete picture of each story. When analyzing content, consider combining metrics—a story with high engagement (both score and comments) from a well-known contributor on a recent timestamp likely represents an important community conversation worth investigating further.
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