Skip to main content

🇨🇭 Part of the Swiss Public Data MCP Portfolio

📡 hn-tech-signal-mcp

Version License: MIT Python 3.11+ MCP No Auth Required CI

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

Demo: Claude using tech_signal_digest across arXiv, HackerNews and GitHub


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     → Six feeds + Algolia search + comment threads
            Lobste.rs      → Curated, lower-noise tech signal
PRACTICE    GitHub Search  → What engineers are actually building right now
            HN Show HN     → What individuals are shipping this week

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.

Within the discourse layer there are two levels of depth. The feeds and the search tell you what is being discussed; hn_discussion tells you what is actually being argued — the counter-arguments and the "we tried this in production" replies that carry the real signal.


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 feeds – top, best, new, Ask HN, Show HN and YC job posts
  • 🔎 HackerNews search – Full history via Algolia, with date range filter
  • 💬 HackerNews comment threads – Read the actual discussion under a story, nested, with a bounded fetch budget
  • 🔧 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 Six feeds: top/best/new/ask/show/job, with score filter
2 hn_search HN Algolia Full-text search across all HN history
3 hn_discussion HackerNews Nested comment thread under a story
4 arxiv_latest arXiv Latest papers by category (cs.AI etc.)
5 arxiv_search arXiv Search papers by keyword/title/author
6 lobsters_hot Lobste.rs Curated tech stories, filterable by tag
7 github_trending_ai GitHub Trending AI repos by topic and stars
8 tech_signal_digest All sources Aggregated Markdown briefing

HackerNews feeds

Feed Content Upstream size
top Front page as ranked right now 500 items
best Highest-voted recent stories 200 items
new Newest submissions, unfiltered 500 items
ask Ask HN — what practitioners are stuck on ~30 items
show Show HN — what people are shipping 200 items
job YC portfolio job posts (type: "job", no comments, score always 1) ~30 items

ask and job are short feeds upstream, so a large limit may return fewer stories than requested.


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) │
                       │  8 Tools                          │────▶│  Lobste.rs JSON API   │
                       │  Stdio | Streamable HTTP          │────▶│  GitHub Search API    │
                       └─────────────────────────────────┘    └───────────────────────┘

Architecture decision

This server uses Architecture A (live API only, two paths per source). There is no bulk dump to fall back on.

Rationale (verified live on 2026-07-28 against the official HackerNews API):

  • All six feed endpoints ({top,best,new,ask,show,job}stories.json) answer HTTP 200 with 29–500 IDs. No auth, no rate-limit headers, Cache-Control: no-cache.
  • HackerNews publishes no bulk export, so caching is entirely this server's responsibility. TTLs live in CACHE_TTL.
  • The Firebase API has no search. Historical and full-text queries go through the Algolia index instead — that is the second path, used by hn_search.
  • item/<id>.json is one request per item. Feeds and comment threads therefore fan out, which is why both are bounded (HN_MAX_CONCURRENCY, max_comments).

Consequences:

  • Every upstream call retries with exponential backoff (2s / 4s / 8s) on network errors, 5xx and 429. Other 4xx fail fast.
  • One process-wide pooled httpx.AsyncClient, closed via the FastMCP lifespan.
  • Unknown item IDs return HTTP 200 with a null body rather than a 404 — hn_discussion translates that into an explicit "no item found" message.

Project Structure

hn-tech-signal-mcp/
├── src/
│   └── hn_tech_signal_mcp/
│       ├── __init__.py
│       ├── server.py          # All 8 tools
│       └── outputs.py         # outputSchema models, one per tool
├── tests/
│   ├── __init__.py
│   └── test_server.py         # 64 unit + 12 live tests
├── pyproject.toml
├── CHANGELOG.md
├── CONTRIBUTING.md
├── LICENSE
├── README.md                  # This file (English)
└── README.de.md               # German version

MCP Protocol Version

This server speaks two protocol eras over the same endpoint. The client's first request on a connection decides which one applies; a later claim from the other era is refused.

Era Revision Who reaches it
initialize handshake 2024-11-05 … 2025-11-25 What today's clients speak. The server answers with the revision asked for, or with the 2025-11-25 ceiling when the request asks for something newer.
Per-request envelope 2026-07-28 A request carrying the 2026-07-28 _meta envelope opens a modern connection.

Both revisions are pinned in tests/test_protocol_version.py and asserted against the installed SDK, so a Dependabot bump of mcp cannot move either one silently.

Spoken, not just named: tests/test_modern_era.py actually connects — in-process in every era (2026-07-28, auto, legacy) and over HTTP with single POSTs, no initialize and no Mcp-Session-Id, against the ASGI app that MCP_TRANSPORT=streamable_http starts. It checks server/discover, tools/list with its freshness hint, tools/call with the Mcp-Name header, the serverInfo stamp in the _meta of every response, and that no feature deprecated by SEP-2577 (sampling, roots, logging) is involved. Two negative controls sit alongside: a wrong Mcp-Method header is rejected with -32020, and the same request under 2025-11-25 still requires a session.

Known, SDK-side: server/discover advertises resources and prompts (with listChanged / subscribe) although this server registers neither — MCPServer always installs those handlers. Switching that off would mean touching private attributes; instead the tests assert that both lists answer empty and without error.

Note that the SDK's LATEST_PROTOCOL_VERSION is an alias for the modern era, not for the handshake era — pinning against it alone would leave the era that current clients actually negotiate free to drift.

Update policy. When the gate fails, do not edit the constant blindly: read the spec changelog between the two revisions, verify the server still behaves, then move the constant, this section, README.de.md and CHANGELOG.md together.


Tool Output

Every tool declares its own outputSchema (closed: additionalProperties: false) from the models in src/hn_tech_signal_mcp/outputs.py, and answers in the three forms the spec separates:

Case content[0].text structuredContent isError
Success The JSON object, pretty-printed The same object false
Source failed [Source] Error: … — true
Unknown or wrong ID (hn_discussion) A sentence saying what to pass instead — true
Digest with some sources down The JSON object, with degraded_sources and a per-source error The same object false

Before, the SDK derived a schema of {"result": string} from the -> str annotation, so structured clients got the JSON as one string field, and every failure arrived as isError: false.

The text stays byte-for-byte what it was — clients that only read text see no change. A response that does not fit its schema is reported as a server defect naming the offending field paths (never the values) instead of reaching the client unvalidated. The recorded fixtures and the daily live run both go through this path, in both protocol eras.


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.
  • HackerNews ask / job feeds: Only ~30 items exist upstream, so a large limit returns fewer stories than requested. Job posts carry type: "job", no comment count, and a score of 1.
  • hn_discussion is always a sample, never the full thread: one request per comment upstream means popular stories (900+ comments) cannot be fetched whole. The budget is split across nesting levels and spread round-robin across sibling threads, so you get a representative cross-section rather than one exhaustively-read sub-thread. Check the truncated flag.
  • hn_discussion comment text is plain text, not HTML: HN's markup is stripped for readability. Do not re-render the output as HTML — the conversion is not a sanitiser.
  • 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


Contributing

See CONTRIBUTING.md (Deutsch).


Security

See SECURITY.md (Deutsch) for the security posture and how to report a vulnerability.


License

MIT License — see LICENSE


Author

Hayal Oezkan · malkreide


Installation

Run via uv's uvx — no clone or manual install needed. Add to your MCP client config (mcpServers for Claude Desktop, Cursor and Windsurf; use a top-level servers key for VS Code in .vscode/mcp.json):

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

Metadata

Release files for hn-tech-signal-mcp 0.5.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for hn-tech-signal-mcp 0.5.0
File Size Uploaded
hn_tech_signal_mcp-0.5.0.tar.gz 227.9 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for hn-tech-signal-mcp 0.5.0
File Interpreter ABI Platform
hn_tech_signal_mcp-0.5.0-py3-none-any.whl Python 3 none any Details

Total release size: 264.0 kB

Release files / hn_tech_signal_mcp-0.5.0.tar.gz

Download URL hn_tech_signal_mcp-0.5.0.tar.gz
Size 227.9 kB
Tags Source
SHA-256 checksum
How to use checksums
92c4cd50e0de10aa5220af4b5590791171d547d5fc0826ebee3a2ac30023cd2f
BLAKE2b-256 checksum
How to use checksums
53f0f2f3b2e36f39ca3ad2c8e092b5377bba046a0a68f12497aae77304fd73c0
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Sep 27, 2026.

Transparency log

Release files / hn_tech_signal_mcp-0.5.0-py3-none-any.whl

Download URL hn_tech_signal_mcp-0.5.0-py3-none-any.whl
Size 36.1 kB
Tags Python 3
SHA-256 checksum
How to use checksums
a4b0feb95a9a899fc89e36a05135c6a970886024a3367b941cbbd3aa2e730152
BLAKE2b-256 checksum
How to use checksums
3ca2a2cd14d5ff7cb4a8ed478c68271e7fac109768df2aec89b5127481e8f00c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Sep 27, 2026.

Transparency log

Release history Release notifications | RSS feed

This release

0.5.0 This release

2 release files

0.4.1

2 release files

0.4.0

2 release files

0.3.0

2 release files

0.2.4

2 release files

0.2.1

2 release files

0.1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page