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Querying Specific Items by ID

Understanding Item IDs

Every piece of content on Hacker News—whether it's a story, comment, poll, or job posting—has a unique numeric identifier. These IDs are permanent and sequential, making them reliable references for retrieving specific content through the MCP server. When you know the exact ID of an item you want to access, querying by ID is the most direct and efficient method available.

How to Query Items by ID

To retrieve a specific item from Hacker News, you simply need to request it using its numeric identifier. You can ask your AI assistant in natural language, such as:

  • "Get Hacker News item 36789012"
  • "Show me the details for HN item ID 36789012"
  • "Retrieve Hacker News post 36789012"

The server will fetch the item and return comprehensive information including its type, title (if applicable), author, timestamp, score, and the full text or URL associated with it.

What You'll Receive

When you query an item by ID, the response includes structured data about that specific piece of content. For stories, you'll receive the title, URL, submission time, author username, current score, and a list of comment IDs attached to it. For comments, you'll get the comment text, author, timestamp, and references to parent items and child comments, allowing you to understand the conversation hierarchy.

This structured format makes it easy to extract exactly the information you need without parsing HTML or navigating through web pages manually.

Finding Item IDs

Item IDs appear in the URL when you browse Hacker News directly. For example, a story URL like news.ycombinator.com/item?id=36789012 indicates the item ID is 36789012. You can also discover IDs through other queries—when you retrieve top stories or user profiles, the responses include item IDs for all referenced content, enabling you to drill down into specific items of interest.

Practical Applications

Querying by ID is particularly useful when you want to:

  • Monitor specific discussions by checking back on a story to see new comments and updated scores
  • Reference particular comments when analyzing expert opinions or technical explanations
  • Track items over time to understand how community engagement evolves
  • Deep-dive into conversations by following comment thread IDs to explore specific sub-discussions

Tips for Effective Use

Keep item IDs saved when you discover content worth tracking. Since IDs are permanent, you can return to the same item days, weeks, or months later to see how discussions have developed or to reference specific insights shared by community members.

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About Metorial

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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