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AI-native HackerNews MCP Server. Find HN content that matters with explainable quality signals.
About
AI-native HackerNews MCP Server. Find HN content that matters with explainable quality signals.
Security Report
Valid MCP server (0 strong, 3 medium validity signals). 5 known CVEs in dependencies (1 critical, 3 high severity) Package registry verified. Imported from the Official MCP Registry.
5 files analyzed · 6 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
How to Install
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-xodn348-readhn": {
"args": [
"readhn"
],
"command": "uvx"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
readhn
AI-native HackerNews MCP Server. Find HN content that matters with explainable quality signals.
What It Does
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%).
Quick Start
# 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.
Usage
Ask your AI agent:
- "Show me top HN stories about Rust this week"
- "Find experts who write about databases on HN"
- "What did practitioners say about Kubernetes networking?"
The agent calls readhn tools, gets results with quality signals, and explains why each result matters.
Configuration (Optional)
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
How It Works
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 comment
Every response includes signals breakdown: why each result was chosen.
License
MIT
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