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Using Natural Language Queries with the Server

Getting Started with Natural Language Queries

The Hacker News MCP Server is designed to work seamlessly with AI assistants that understand natural language. Instead of memorizing commands or API endpoints, you can simply ask questions or make requests in plain English, and your assistant will interact with the server on your behalf.

Basic Query Patterns

Start with straightforward requests to explore what's happening on Hacker News. Try asking:

  • "What are the top stories on Hacker News right now?"
  • "Show me the newest submissions"
  • "What are today's best stories?"

Your AI assistant will translate these requests into the appropriate server calls and present the results in an easy-to-read format, including story titles, scores, authors, and links.

Exploring Stories and Comments

To dive deeper into specific content, reference stories by their characteristics or request comment threads:

  • "Show me comments on the top story about AI"
  • "What are people saying about [specific topic]?"
  • "Get the discussion thread for the story about [company/technology]"

The server retrieves complete comment threads, allowing you to follow conversations and understand different perspectives within the community.

Researching Users and Activity

When you need information about specific Hacker News community members, use natural queries like:

  • "Get the profile for user [username]"
  • "What has [username] been commenting about recently?"
  • "Show me the karma and activity for [username]"

This is particularly useful for identifying subject matter experts or tracking contributions from thought leaders in specific technical domains.

Combining Queries for Analysis

The real power emerges when you chain multiple queries together. You might ask your assistant to "find the top story about machine learning and show me what the highest-voted comments are saying." The assistant can execute multiple server operations in sequence, gathering stories and then retrieving relevant comment data.

Tips for Effective Queries

Be specific when you can—mentioning particular topics, users, or story types helps your assistant retrieve exactly what you need. However, the server works equally well with general exploratory questions like "what's trending in tech today?"

You can also request comparative analysis: "Compare the community reaction to these two stories" or temporal queries: "What were the top stories earlier this week?"

Working with Results

Once you receive results, you can ask follow-up questions naturally. If a story interests you, simply say "show me the comments on that" or "tell me more about the author." Your assistant maintains context from previous queries, making exploration intuitive and conversational.

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