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Comment threads on Hacker News contain some of the most valuable insights and technical discussions on the internet. The Hacker News MCP server makes it easy to access and navigate these conversations programmatically, allowing you to explore discussions without manually browsing the website.
To retrieve a specific comment, you'll need its unique item ID. Each comment on Hacker News has a distinct numerical identifier that you can use to fetch its content directly. Simply request the comment by ID through your AI assistant, and the server will return structured data including the comment text, author, timestamp, score, and relationships to parent comments or the original story.
When you retrieve a comment, you'll receive information about its position in the conversation hierarchy. This includes references to the parent item (either another comment or the original story) and any child comments that form replies to it.
Hacker News discussions are organized as threaded conversations, where replies create nested structures. The server provides access to these relationships, allowing you to traverse entire comment trees systematically.
Start by requesting a story's details, which includes references to all top-level comments. From there, each comment contains references to its replies, enabling you to walk through the conversation tree. This hierarchical structure preserves the natural flow of discussion, making it easy to understand who's responding to whom and how conversations branch into sub-topics.
To explore an entire discussion thread, begin by retrieving the story itself. The story data includes a list of comment IDs representing the top-level comments. You can then fetch each of these comments individually, and recursively retrieve their children to build a complete picture of the conversation.
This approach gives you flexibility in how deeply you want to explore discussions. You might choose to only examine top-level comments for a high-level overview, or dive into specific conversation branches that seem particularly relevant to your interests.
When working with large discussion threads, consider focusing on highly-scored comments first, as these typically contain the most valuable or well-received contributions. Pay attention to timestamps to understand how conversations evolved over time, and note comment authors to identify consistent contributors or domain experts.
The server handles all the complexity of API interactions, so you can focus on analyzing the content rather than managing technical details.
The Polar Signals integration lets you query and analyze continuous profiling data to identify performance bottlenecks, investigate CPU and memory usage patterns, and optimize your application's resource consumption directly from your workflow.
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