OpenMesh

Connect AI Agents to
OpenMesh

Automate workflows and connect AI agents to OpenMesh. Metorial is built for developers. Handling OAuth, compliance, observability, and more.

Back to OpenMesh overview

Querying Specific Stories and Items by ID

Overview

When you need to access specific content on Hacker News, querying by ID is the most direct and efficient method. Every story, comment, and poll on Hacker News has a unique identifier that allows you to retrieve it instantly. This article explains how to use the OpenMesh MCP server to query specific items using their IDs.

Understanding Hacker News IDs

Each piece of content on Hacker News—whether it's a story, comment, poll, or job posting—is assigned a unique numeric ID when it's created. These IDs are sequential and permanently associated with that item. You'll often encounter these IDs in Hacker News URLs (for example, news.ycombinator.com/item?id=12345678) or when browsing story feeds that include ID information in their metadata.

Querying Stories by ID

To retrieve a specific story, simply request it by its ID through your AI assistant. You might say something like "Get Hacker News story 35123456" or "Show me the details for HN item 35123456." The server will return comprehensive information about that story, including:

  • Title and URL
  • Author (submitter) username
  • Score (points)
  • Submission time
  • Number of comments
  • Comment IDs for further exploration

This is particularly useful when you've found an interesting story elsewhere and want to see its current score, read its comments, or check how the community has received it.

Accessing Comments by ID

Comments work the same way. Each comment has its own unique ID, which you can use to retrieve that specific comment along with its metadata. Request a comment by asking for it directly: "Get Hacker News comment 35123457."

The response includes the comment text, author, timestamp, score, and crucially, the IDs of any child comments (replies). This allows you to traverse entire comment threads by following the parent-child relationships between comments.

When to Use ID-Based Queries

ID-based queries are ideal when you:

  • Have a specific URL from Hacker News and want detailed information
  • Need to track a particular story or comment over time to monitor score changes or new replies
  • Want to retrieve a comment thread starting from a specific comment
  • Are following up on references to specific HN items in other contexts
  • Need to access older content that's no longer on the front page

Practical Examples

If you're monitoring a product launch, you might track the submission ID to check periodically how the discussion is evolving. If you're researching a technical topic, you might save IDs of particularly insightful comments to reference later. The direct access that ID-based querying provides makes these workflows simple and reliable.

By understanding how to query specific items by ID, you can navigate Hacker News content precisely and efficiently, accessing exactly what you need without browsing through lists or search results.

OpenMesh on Metorial

The OpenMesh integration lets you query, analyze, and manipulate mesh data structures directly through natural language, enabling you to inspect vertices, edges, faces, and perform geometric operations without writing code.

Connect anything. Anywhere.

Ready to build with Metorial?

Let's take your AI-powered applications to the next level, together.

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.

Star us on GitHub