mcpField
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readhn

readhn

Local
github.com/xodn348Social Media5Updated 33w ago
Repository

About readhn

readhn is an MCP server for AI agents to discover Hacker News stories and domain experts. It ranks results with quality signals that explain why they were selected.

Key features

  1. 01Filter stories by keywords, score, and time
  2. 02Find domain experts using EigenTrust
  3. 03Analyze comment threads and quality
  4. 04Explain rankings with quality signals

Use cases

  1. 01Find this week's top Rust stories
  2. 02Locate database experts on HN
  3. 03Review practitioner views on Kubernetes networking

MCP support

readhn exposes tools for story discovery, search, expert finding, user and story briefs, and thread analysis to MCP clients.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
  "mcpServers": {
    "xodn348-readhn": {
      "command": "uvx",
      "args": [
        "readhn"
      ]
    }
  }
}
Run commanduvx readhn

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypireadhn0.2.0

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

readhn

PyPI Tests Coverage MCP

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 signals
  • search() — Algolia search with explainable ranking
  • find_experts() — Find domain experts using EigenTrust on comment graph
  • expert_brief() — User profile + activity + trust score
  • story_brief() — Story + top comments + signals in one call
  • thread_analysis() — Full comment tree with quality signals per comment

Every response includes signals breakdown: why each result was chosen.

License

MIT

Comments

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