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Accessing and Navigating Comment Threads

Understanding Comment Threads

Comments on Hacker News often contain the most valuable insights, with community members providing expert analysis, alternative perspectives, and technical deep-dives that rival the original submissions. The Hacker News MCP server makes accessing and navigating these discussion threads straightforward, allowing you to explore conversations without manual browsing.

Accessing Comments for a Story

To retrieve comments for a specific story, you'll need the story's unique identifier. Once you have this ID, simply request the comment thread through your AI assistant. For example, you might ask "Show me the comments for story 12345678" or "What are people saying about this Hacker News post?"

The server will return structured comment data that includes the comment text, author information, timestamps, scores, and importantly, the hierarchical relationships between comments. This structure preserves the threaded nature of Hacker News discussions.

Navigating Comment Hierarchies

Hacker News comments are organized in a tree structure, where replies appear as children of parent comments. The server preserves this hierarchy, allowing you to understand conversation flow and see which comments respond to others.

When you request a comment thread, you'll receive information about parent-child relationships. This enables you to follow specific conversation branches, identify which comments generated the most discussion, or focus on particular subtopics within a larger thread.

Retrieving Individual Comments

Sometimes you'll want to access a specific comment directly rather than an entire thread. Each comment has its own unique identifier, and you can request individual comments using these IDs. This is particularly useful when someone references a specific insightful comment, or when you want to check if there have been replies to a comment you're tracking.

Working with Comment Data

Each comment includes several useful data points: the comment text itself, the username of the author, when the comment was posted, its score (if available), and references to parent and child comments. This information lets you assess comment quality, understand timing of responses, and identify prolific or influential commenters.

Practical Tips

When exploring comment threads, start with the top-level comments to get an overview of the main discussion themes. Then drill down into specific branches that interest you. Remember that highly-scored comments often contain particularly valuable insights, though newer comments may not have accumulated votes yet.

For lengthy threads, consider requesting specific sections or focusing on comments from users known to have expertise in the topic area. The server's flexibility allows you to navigate large discussions efficiently without information overload.

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Metorial provides developers with instant access to 600+ MCP servers for building AI agents that can interact with real-world tools and services. Built on MCP, Metorial simplifies agent tool integration by offering pre-configured connections to popular platforms like Google Drive, Slack, GitHub, Notion, and hundreds of other APIs. Our platform supports all major AI agent frameworks—including LangChain, AutoGen, CrewAI, and LangGraph—enabling developers to add tool calling capabilities to their agents in just a few lines of code. By eliminating the need for custom integration code, Metorial helps AI developers move from prototype to production faster while maintaining security and reliability. Whether you're building autonomous research agents, customer service bots, or workflow automation tools, Metorial's MCP server library provides the integrations you need to connect your agents to the real world.

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