🇨🇭 Part of the Swiss Public Data MCP Portfolio

📡 hn-tech-signal-mcp

MCP server for global tech & AI signal intelligence — aggregates HackerNews, arXiv, Lobste.rs and GitHub into a structured briefing. No API key required.

🇩🇪 Deutsche Version

Demo

---

Overview

hn-tech-signal-mcp turns any AI assistant into a proactive tech intelligence analyst. The server aggregates four signal layers — research frontier, developer discourse, curated signal, and open-source practice — into a single, structured briefing.

No authentication required. All four data sources are public APIs. Optional: set GITHUB_TOKEN for higher GitHub rate limits (5,000 req/h vs. 60 req/h unauthenticated).

Anchor demo query: "Give me a tech signal digest on AI today — what is happening in research, developer discourse and open source?"

---

Signal Architecture

FRONTIER    arXiv API      → Latest AI/ML papers (cs.AI, cs.LG, cs.CL, cs.CV)
DISCOURSE   HackerNews     → Top/best stories + Algolia full-text search
            Lobste.rs      → Curated, lower-noise tech signal
PRACTICE    GitHub Search  → What engineers are actually building right now

Think of the four layers as a radar: arXiv shows what's coming over the horizon, HN and Lobste.rs show what practitioners are discussing, and GitHub shows what teams are actually shipping.

---

Features

• 🔬 Research frontier – Latest arXiv papers by category (cs.AI, cs.LG, cs.CL, and more)
• 🔍 arXiv full-text search – Find papers by keyword, title, or author
• 🗣️ HackerNews top/best/new – With optional AI-keyword filter
• 🔎 HackerNews search – Full history via Algolia, with date range filter
• 🔧 Lobste.rs hottest – Curated developer signal, filterable by tag
• 🛠️ GitHub trending AI repos – Search by topic, stars, sort by activity or popularity
• 📋 Tech signal digest – One-call cross-source briefing in Markdown
• ☁️ Dual transport – stdio for Claude Desktop, Streamable HTTP for cloud deployment

#	Tool	Source	Description
1	hn_top_stories	HackerNews	Top/best/new stories, with optional AI filter
2	hn_search	HN Algolia	Full-text search across all HN history
3	arxiv_latest	arXiv	Latest papers by category (cs.AI etc.)
4	arxiv_search	arXiv	Search papers by keyword/title/author
5	lobsters_hot	Lobste.rs	Curated tech stories, filterable by tag
6	github_trending_ai	GitHub	Trending AI repos by topic and stars
7	tech_signal_digest	All sources	Aggregated Markdown briefing

---

Prerequisites

• Python 3.11+
• uv or pip
• No API key required
• Optional: GITHUB_TOKEN for higher GitHub rate limits

---

Installation

# Recommended: uvx (no install step needed)
uvx hn-tech-signal-mcp

# Alternative: pip
pip install hn-tech-signal-mcp

---

Quickstart

# Start the server (stdio mode for Claude Desktop)
uvx hn-tech-signal-mcp

# With optional GitHub token for higher rate limits
GITHUB_TOKEN=ghp_yourtoken uvx hn-tech-signal-mcp

Try immediately in Claude Desktop:

"Give me a tech signal digest on AI today" "What are the latest cs.AI papers from the last 48 hours?" "What is HackerNews discussing about MCP this week?" "Show me trending GitHub repos for the topic 'ai-agents'"

---

Configuration

Environment Variables

Variable	Default	Description
GITHUB_TOKEN	–	Optional. GitHub personal access token. Without it: 60 req/h. With it: 5,000 req/h. The token is only sent to api.github.com, never to other upstreams.
MCP_TRANSPORT	stdio	Transport: stdio or streamable_http
MCP_HOST	127.0.0.1	Bind host for HTTP transport. Non-loopback values require MCP_BEARER_TOKEN.
MCP_PORT	8000	Port for HTTP transport
MCP_BEARER_TOKEN	–	Required when MCP_HOST is not loopback. Shared secret to gate the HTTP endpoint.

Claude Desktop Configuration

{
  "mcpServers": {
    "hn-tech-signal": {
      "command": "uvx",
      "args": ["hn-tech-signal-mcp"],
      "env": {
        "GITHUB_TOKEN": "ghp_yourtoken_optional"
      }
    }
  }
}

Config file locations:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

After restarting Claude Desktop, all 7 tools are available.

Cloud Deployment (Streamable HTTP)

For use via claude.ai in the browser (e.g. on managed workstations):

Render.com (recommended):

1. Push/fork the repository to GitHub
2. On render.com: New Web Service → connect GitHub repo
3. Optionally set GITHUB_TOKEN in the Render dashboard
4. In claude.ai under Settings → MCP Servers, add: https://your-app.onrender.com/mcp

# Local HTTP mode (binds 127.0.0.1 by default)
MCP_TRANSPORT=streamable_http MCP_PORT=8000 python -m hn_tech_signal_mcp.server

# Public bind (requires bearer token, intended behind a reverse proxy that terminates TLS)
MCP_TRANSPORT=streamable_http \
MCP_HOST=0.0.0.0 \
MCP_BEARER_TOKEN="$(openssl rand -hex 32)" \
python -m hn_tech_signal_mcp.server

Hardening: the server refuses to bind to non-loopback hosts unless MCP_BEARER_TOKEN is set. Run cloud deployments behind a TLS-terminating reverse proxy (Render, Fly, Caddy, …) and treat MCP_BEARER_TOKEN as the shared client secret your proxy enforces.

---

Architecture

┌─────────────────┐    ┌─────────────────────────────────┐    ┌───────────────────────┐
│  Claude / AI    │────▶│   HN Tech Signal MCP             │────▶│  HackerNews Firebase  │
│  (MCP Host)     │◀────│   (MCP Server)                   │────▶│  HN Algolia Search    │
└─────────────────┘    │                                   │────▶│  arXiv.org (Atom API) │
                       │  7 Tools                          │────▶│  Lobste.rs JSON API   │
                       │  Stdio | Streamable HTTP          │────▶│  GitHub Search API    │
                       └─────────────────────────────────┘    └───────────────────────┘

---

Project Structure

hn-tech-signal-mcp/
├── src/
│   └── hn_tech_signal_mcp/
│       ├── __init__.py
│       └── server.py          # All 7 tools
├── tests/
│   ├── __init__.py
│   └── test_server.py         # 21 unit + 5 live tests
├── pyproject.toml
├── CHANGELOG.md
├── CONTRIBUTING.md
├── LICENSE
├── README.md                  # This file (English)
└── README.de.md               # German version

---

Testing

# Unit tests (no network required)
PYTHONPATH=src pytest tests/ -m "not live"

# Live integration tests (requires network)
PYTHONPATH=src pytest tests/ -m "live"

---

Example Use Cases

KI-Fachgruppe / AI Working Group

"Give me a tech signal digest on AI today"
→ tech_signal_digest(focus="AI")

"What are the top 5 arXiv papers on LLM agents this week?"
→ arxiv_search(query="LLM agents", category_filter="cs.AI", limit=5)

"What is HackerNews discussing about model context protocol?"
→ hn_search(query="model context protocol", days_back=30)

Research Monitoring

"Show me the latest NLP papers from arXiv"
→ arxiv_latest(category="cs.CL", limit=10)

"Search arXiv for papers on retrieval-augmented generation"
→ arxiv_search(query="retrieval augmented generation RAG", limit=10)

Open Source Intelligence

"What AI agent frameworks are trending on GitHub?"
→ github_trending_ai(topic="ai-agents", sort="updated", limit=10)

"Show me the most starred MCP-related repos"
→ github_trending_ai(topic="mcp", sort="stars", min_stars=50)

[→ More use cases by audience →](EXAMPLES.md)

---

arXiv Category Reference

Category	Full Name	Key Topics
cs.AI	Artificial Intelligence	Agents, planning, knowledge representation
cs.LG	Machine Learning	Training, optimisation, generalisation
cs.CL	Computation & Language	NLP, LLMs, translation, summarisation
cs.CV	Computer Vision	Image recognition, generation, multimodal
cs.RO	Robotics	Embodied AI, navigation
stat.ML	Statistics ML	Probabilistic methods, Bayesian ML

---

Rate Limits

Source	Auth Required	Limit
HackerNews Firebase	No	Very generous (Firebase)
HN Algolia Search	No	~10,000 req/hour
arXiv	No	~3 req/second (be respectful)
Lobste.rs	No	Reasonable use
GitHub Search	No	60 req/hour
GitHub Search	GITHUB_TOKEN	5,000 req/hour

---

Known Limitations

• GitHub rate limit: 60 req/h without token. Set GITHUB_TOKEN for production use.
• arXiv: Papers may take up to 24h to appear after submission. Weekends/holidays have delayed batches.
• HackerNews: Top/best story lists update every few minutes. Very new stories may have low scores.
• Lobste.rs: Smaller community than HN; tech-focused but may not cover all AI topics.
• tech_signal_digest: Makes ~4 concurrent requests; if one source is slow it may delay the full response.

---

Synergies with Other MCP Servers

hn-tech-signal-mcp combines well with:

Combination	Use Case
+ news-monitor-mcp	Global research + Swiss institutional media coverage
+ fedlex-mcp	Tech discourse + Swiss regulatory context
+ global-education-mcp	AI research trends + education policy data
+ swiss-statistics-mcp	Tech landscape + Swiss economic/structural data

---

Safety & Limits

• Read-only: All tools perform HTTP GET requests only — no posts, comments, votes, or writes are issued upstream.
• No personal data: The server queries public tech aggregators. No PII is collected; author handles in public posts/papers are returned as-is from upstream and never enriched or cross-referenced.
• Rate limits: See the Rate Limits table. arXiv's ≤3 req/sec guidance is respected by default; GitHub search is capped at 60 req/h without a GITHUB_TOKEN. A request timeout is enforced per call.
• No bulk harvesting: This server is built for interactive, conversational use — not for scraping or mirroring. Do not use it to bypass upstream pagination or ToS limits.
• Terms of service: Data is subject to the ToS of each source — HackerNews, arXiv API, Lobste.rs, GitHub.
• No guarantees: Community project, not affiliated with HackerNews / Y Combinator, arXiv / Cornell, Lobste.rs, or GitHub. Availability depends on upstream APIs.

---

Changelog

See CHANGELOG.md

---

License

MIT License — see LICENSE

---

Author

Hayal Oezkan · malkreide

---

Credits & Related Projects

• HackerNews API: hacker-news.firebaseio.com — Y Combinator / Firebase
• arXiv API: export.arxiv.org — Cornell University / arXiv.org
• Lobste.rs API: lobste.rs — community-run
• GitHub API: api.github.com — GitHub / Microsoft
• Protocol: Model Context Protocol — Anthropic / Linux Foundation
• Related: news-monitor-mcp — Swiss institutional media monitoring
• Portfolio: Swiss Public Data MCP Portfolio