Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"io-github-xodn348-readhn": {
"args": [
"readhn"
],
"command": "uvx"
}
}
}Are you the author?
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AI-native HackerNews MCP Server. Find HN content that matters with explainable quality signals.
Run this in your terminal to verify the server starts. Then let us know if it worked — your result helps other developers.
uvx 'readhn' 2>&1 | head -1 && echo "✓ Server started successfully"
After testing, let us know if it worked:
Five weighted categories — click any category to see the underlying evidence.
No known CVEs.
Checked readhn against OSV.dev.
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AI-native HackerNews MCP Server. Find HN content that matters with explainable quality signals.
Discover — Filter stories by keywords, scores, time. Get ranked results with quality signals.
Trust — Find domain experts. See who's talking and why they matter. EigenTrust propagation from seed experts.
Understand — Every result explains WHY. 5 signals: practitioner depth (30%), thread depth (20%), expert involvement (20%), velocity (15%), references (15%).
# Install
pip install readhn
# Auto-configure supported AI agents
readhn setup
readhn setup detects Claude Code, Codex, Cursor, Claude Desktop, Cline, Windsurf, and OpenCode config paths and adds the readhn MCP server.
Useful setup flags:
readhn setup --list # Show detected agents
readhn setup --dry-run # Preview config changes only
readhn setup --agents "Cursor" # Configure only specific agents
After setup, your AI agent auto-discovers readhn and uses it when you ask HN questions.
Ask your AI agent:
The agent calls readhn tools, gets results with quality signals, and explains why each result matters.
export HN_KEYWORDS="ai,llm,rust,distributed-systems,databases" # Default filter keywords
export HN_MIN_SCORE="50" # Minimum story score
export HN_EXPERTS="tptacek,simonw,antirez,ept,jepsen" # Seed experts for trust
export HN_TIME_HOURS="24" # Time window
When you ask HN questions, your AI agent uses these tools:
discover_stories() — Top stories filtered by keywords/score/time, ranked by quality signalssearch() — Algolia search with explainable rankingfind_experts() — Find domain experts using EigenTrust on comment graphexpert_brief() — User profile + activity + trust scorestory_brief() — Story + top comments + signals in one callthread_analysis() — Full comment tree with quality signals per commentEvery response includes signals breakdown: why each result was chosen.
MIT