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Comment threads on Hacker News often contain the most valuable insights and technical discussions. The MCP server makes it easy to access and navigate these conversations, allowing you to explore community perspectives and expert commentary without manually browsing the website.
To access a specific comment, you'll need its unique identifier. Simply ask your AI assistant to retrieve the comment by its ID, and the server will return structured information including the comment text, author, timestamp, score, and its position within the thread hierarchy. This is particularly useful when you have a direct link to a comment or want to examine specific responses in a discussion.
Comments on Hacker News are organized in threaded conversations, with replies nested under parent comments. When you retrieve a comment, the server provides information about its relationships within the thread—which comment it's responding to and which comments are responding to it. You can traverse these comment trees by requesting child comments, allowing you to follow specific conversation branches that interest you.
To explore an entire discussion, start by requesting the story or top-level item, then navigate through its comments. Ask your assistant to show you the main comments on a story, or dive deeper into specific threads by requesting replies to particular comments.
When researching a topic, you'll want to locate comment threads where that subject is being discussed. Start by retrieving stories related to your area of interest, then examine their comment sections. You can ask your assistant to summarize key points from comment threads or identify particularly insightful contributions based on score or author reputation.
Comments make the most sense when viewed in context. When examining a specific comment, you can request its parent comment to understand what it's responding to, or retrieve the original story to see what sparked the entire discussion. This contextual navigation helps you grasp the full scope of a conversation without getting lost in fragmented exchanges.
Focus on highly-scored comments first—these typically represent well-reasoned or particularly insightful contributions that the community has validated. Pay attention to comment timestamps to understand how discussions evolve over time. If you're researching a specific user's perspective, you can access their profile to see all their comments across different threads.
The server handles all the complexity of mapping thread relationships and retrieving nested data, so you can focus on understanding the conversations rather than managing API calls.
The Supabase integration lets you query and manage your database, authentication, and storage directly from your AI assistant, enabling natural language database operations and real-time data access.
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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.