That led me to build readhn, an MCP server that helps with three things:
- Discover: find relevant stories/comments by keyword, score, and time window
- Trust: identify credible voices using EigenTrust-style propagation from seed experts
- Understand: show why each result is ranked, with explicit signals instead of a black-box score
It includes 6 tools: discover_stories, search, find_experts, expert_brief, story_brief, and thread_analysis.
I also added readhn setup so AI agents can auto-configure it (Claude Code, Codex, Cursor, and others) after pip install.
I’d love feedback on:
1) whether these ranking signals match how you evaluate HN quality,
2) trust-model tradeoffs,
3) what would make this useful in your daily workflow.
If this is useful to you, starring the repo helps others discover it: https://github.com/xodn348/readhn
