Model-Context-Protocol (MCP) server that exposes Hacker News data (stories, comments, users) through 4 tools: get_stories, get_story_info, search_stories and get_user_info.
https://github.com/erithwik/mcp-hnSkip the endless scrolling through HN tabs. This MCP server pipes Hacker News data directly into your AI conversations, so you can query stories, analyze comment threads, and research user activity without leaving your workflow.
You're already checking Hacker News daily for industry insights, technical discussions, and career opportunities. But manually browsing, bookmarking, and cross-referencing stories breaks your focus. This server solves that by making HN data queryable through natural language.
Instead of opening browser tabs and losing context, you ask questions like:
Your AI can now fetch the data, analyze patterns, and synthesize insights from both articles and community discussion.
Story Intelligence: Pull top, new, Ask HN, or Show HN stories with full metadata. Search across the entire HN archive using natural language queries.
Comment Analysis: Get complete comment threads for any story. Perfect for understanding community sentiment or finding expert opinions buried in discussions.
User Research: Profile any HN user to understand their posting history, expertise areas, and contribution patterns.
Cross-Platform Integration: Combine with other MCP servers (like Puppeteer) to read linked articles and analyze both the source content and HN discussion in one conversation.
Technical Research: "Find HN discussions about PostgreSQL performance tuning from the last month, summarize the main optimization strategies mentioned in comments."
Competitive Analysis: "What has the HN community been saying about Vercel vs Netlify? Focus on developer experience feedback."
Hiring Intelligence: "Show me Ask HN posts about engineering management challenges and highlight recurring themes."
Industry Trends: "Track mentions of 'AI agent' in HN titles over time and analyze the evolution of discussion topics."
Works seamlessly with Claude Desktop through a single config update. No API keys, no complex setup, no rate limit headaches - just point it at the public HN Firebase API and start querying.
The server exposes four focused tools that handle the complexity of HN's data structure, so your AI conversations stay natural while accessing rich, structured data from stories, comments, and user profiles.
{
"mcpServers": {
"mcp-hn": {
"command": "uvx",
"args": ["mcp-hn"]
}
}
}
This isn't just about reading HN faster - it's about making HN data part of your research and decision-making process. Connect trends across months of discussions, identify domain experts by their comment quality, or build reading lists based on community engagement patterns.
When combined with other MCP servers, you can create research workflows that pull HN discussions, fetch the actual articles, and synthesize both perspectives into actionable insights.
Your AI becomes a research assistant that understands both what the tech community is discussing and why those discussions matter to your work.