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Comment threads on Hacker News contain some of the most valuable insights and technical discussions in the tech community. The Hacker News MCP Server makes it easy to access and navigate these conversations programmatically through your AI assistant, without needing to manually browse the website or write custom code.
To view comments on a specific Hacker News story, you'll need the story's unique identifier. You can obtain this ID when retrieving stories from feeds like top stories or new submissions. Once you have the ID, simply ask your AI assistant to retrieve the comments for that item.
The server returns structured comment data including the comment text, author, timestamp, score, and importantly, the hierarchical relationships between comments. This structure preserves the threaded nature of Hacker News discussions, showing which comments are replies to others.
Hacker News comments are organized in a tree structure where replies are nested under parent comments. When you retrieve a comment, the server provides information about its child comments (replies), allowing you to traverse the entire discussion thread.
To explore a conversation deeply, you can start with the top-level comments on a story and progressively request child comments to move deeper into specific discussion branches. This approach is particularly useful when you're interested in a specific debate or technical explanation that spans multiple replies.
If you already know a specific comment's ID—perhaps from previous exploration or external reference—you can retrieve it directly. This gives you immediate access to that comment's content and metadata without needing to traverse from the story level.
When working with large comment threads, consider focusing on high-scoring comments first, as these typically contain the most valued insights from the community. You can identify these through the score information provided with each comment.
For time-sensitive monitoring, remember that the server provides real-time access to comments. New replies appear as they're posted, making it possible to follow developing discussions as they unfold.
A typical workflow might involve retrieving a trending story, examining its top-level comments to understand the general community response, then diving into specific comment branches that contain detailed technical discussions or expert opinions. This layered approach helps you efficiently extract relevant information from extensive conversation threads without becoming overwhelmed by the full volume of comments.
The Cloudflare Audit Logs integration lets you query and analyze account activity, user actions, and configuration changes across your Cloudflare organization for security monitoring and compliance tracking.
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