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Comment threads on Hacker News contain some of the most valuable insights and technical discussions on the platform. The MCP server makes it easy to access and navigate these conversations programmatically through your AI assistant.
To access a specific comment, you'll need its unique identifier. Simply ask your assistant to retrieve the comment by its ID, and the server will return structured information including the comment text, author, timestamp, score, and any child comments. This is particularly useful when you want to examine a specific piece of commentary that's been referenced or shared.
Comments on Hacker News are organized in threaded conversations, where replies create nested hierarchies. When you retrieve a comment, the server provides information about its position in the thread, including references to parent comments and child replies. This structure allows you to navigate up and down the conversation tree, understanding the full context of any discussion.
To explore an entire thread, start by requesting the story item itself, which contains references to all top-level comments. From there, you can traverse the tree by following the child comment references, building a complete picture of the conversation.
The most common way to access comments is through the story they're attached to. When you request a story, the server returns metadata that includes an array of comment IDs associated with that submission. You can then request these comments individually or ask your assistant to summarize the discussion, and the server will handle retrieving the relevant comment data.
Each comment includes valuable metadata beyond just the text content. You'll receive information about the comment's score (how many upvotes it has received), when it was posted, who authored it, and whether it's been flagged or is dead (removed or killed by moderators). This metadata helps you assess the community's reception of the comment and the credibility of the discussion.
When working with large comment threads, start by examining top-level comments first, as these typically contain the most substantial responses. Look at comment scores to identify contributions the community found valuable. If you're researching a specific topic, ask your assistant to search for comments containing relevant keywords within a thread.
For deep discussions with many nested replies, consider requesting specific branches of the conversation tree rather than the entire thread at once. This focused approach makes it easier to follow particular lines of discussion without getting overwhelmed by parallel conversations.
The Firecrawl integration lets you scrape websites, extract structured data, and convert web pages into LLM-ready formats directly from your MCP-enabled applications.
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