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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 provides structured access to these conversations, allowing you to explore discussions programmatically without manual browsing.
To access comments on a specific story, you'll need the story's unique identifier. Once you have this ID, simply request the comments associated with that item. The server will return the complete comment thread, including all nested replies and discussion branches.
You can ask your AI assistant questions like "Show me the comments on story 12345678" or "What are people saying about this submission?" The server handles the API calls and presents the comments in an organized, readable format.
Hacker News comments are organized hierarchically, with replies nested under parent comments to form conversation threads. The server preserves this tree structure, making it easy to follow discussion flows and understand context.
Each comment includes several key pieces of information:
This structured data allows you to trace conversations from top-level comments down through multiple reply levels, helping you identify the most engaged discussion branches.
If you know a specific comment's ID, you can retrieve it directly without pulling the entire thread. This is useful when you want to reference particular insights or track how specific comments perform over time.
Comment threads vary widely in depth and engagement. Some stories generate hundreds of comments across multiple discussion levels, while others receive minimal response. The server provides access to all comments regardless of thread depth, enabling you to:
When working with comment threads, start with top-level comments to get an overview of the discussion's main themes. From there, dive into specific branches that align with your interests or research needs.
For stories with extensive discussions, consider filtering or focusing on highly-scored comments first, as these often contain the most valuable insights or widely-agreed perspectives.
Remember that comments load with their complete metadata, so you can always identify comment authors and explore their profiles if you discover particularly insightful contributors.
The Google Drive integration lets you search, read, create, and manage files and folders in your Drive directly through AI interactions. Use it to organize documents, retrieve file contents, share files, and automate common Drive tasks without switching to your browser.
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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.