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