Hacker News Intelligence 🟠

foXLabs web & community series: GitHub trending · Wikipedia companies · Community listening

🎉 Turn Hacker News into clean, structured intelligence — no login, no API key, one row per item, with the title, author, points, comments and links. Built for developer-tool marketing, hiring and tech research.

🔍 What is the Hacker News Intelligence — and when should you use it?

Give this actor keywords or topics and it returns matching items from public Hacker News posts and comments — as clean, deduplicated rows you can filter, export or feed to an AI agent. Every run reads the source live.

Use it when you need: a HN item company list for outreach; formation / status monitoring; or a canonical registry record for KYB and due diligence.

Use something else when: you need private analytics — this reads public Hacker News content only.

🤖 Use with AI agents

Already on the Apify MCP server? Ask for this Actor by name: foxlabs/hackernews-intelligence.

Your agent can pay for its own runs. This Actor is pay-per-event with agentic payments, so an agent can discover it, run it and settle the bill over x402 (USDC on Base) or Skyfire — no Apify account or API token of its own. Billing is the same either way: per delivered record, never for errors.

Otherwise paste this into Claude, ChatGPT, Cursor or any MCP-enabled assistant:

I want to pull HN item company records using the Apify Actor `foxlabs/hackernews-intelligence`.
Input: `mode`, `query`, `searchType`, `sortBy` and more — see the Input table below. `maxResults` caps how many results are returned.
Start with: {"mode":"who_is_hiring","maxResults":1000}
Ask me what to look up, run the Actor, then summarise the rows as a table.

The machine-readable API, MCP config and OpenAPI definition live at apify.com/foxlabs/hackernews-intelligence.md.

📋 Overview

Everything you need to turn public Hacker News posts and comments into clean, structured data — in one actor, with no login, cookies or API key.

Why teams pick this actor:

• ✅ Whole feed, one call — name or ID in, matching items out.
• 🧹 No empty-promise columns — only fields this registry actually fills; degenerate columns are removed.
• 🔗 Stable identifiers — every row carries the source's own IDs, ready to join across runs and to other Fox Labs actors.
• 💰 Per-row pricing — a minimal price per delivered row, no subscription.
• 🤖 Agent-ready — MCP + x402 agentic payments.

✨ Features

• 🔍 Name or ID lookup — relevance-ranked name search or exact registry-ID lookup.
• 🏢 Full entity profile — status, legal form, formation date, address and the registry’s own contact fields.
• 🧹 Clean schema — deduplicated camelCase rows, ready for CSV/Excel/JSON.

🎬 Quick Start

curl -X POST "https://api.apify.com/v2/acts/foxlabs~hackernews-intelligence/runs?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"mode":"who_is_hiring","maxResults":1000}'

🚀 Getting Started (3 steps)

1. Choose your targets — keywords or topics.
2. Set the cap — maxResults limits how many results are returned.
3. Run and export — get a clean dataset as JSON, CSV or Excel.

📥 Input

{"mode":"who_is_hiring","maxResults":1000}

Field	Type	Description
mode	string	Search = query the full HN archive (stories & comments) with points/date filters — unlimited depth, no 1,000-result wall. Who is hiring = parse the monthly 'Ask…
query	string	Search mode. What to search for — a brand, product, topic (e.g. "postgres", "Supabase", "rust async"). Leave empty to browse everything in the date window.
searchType	string	Search mode. Stories = titles/links (launches, articles). Comments = the discussion text (where brand mentions and opinions actually live). Both = the two merged.
sortBy	string	Date (default) streams newest-first with UNLIMITED depth. Relevance uses the API's ranked order but is hard-capped at 1,000 results by the API.
minPoints	integer	Search mode, stories only. Keep only stories with at least this many upvotes (e.g. 100 = front-page material). Leave empty for all.
minComments	integer	Search mode, stories only. Keep only stories with at least this many comments. Leave empty for all.
author	string	Search mode. Only items by this HN username (e.g. "patio11"). Leave empty for all authors.
threadType	string	Which monthly thread to parse: companies hiring (default), people looking for work, or the freelancer thread.
month	string	Which month's thread, e.g. 2026-07. Leave empty for the latest thread.
datePreset	string	Search mode: how far back to search. The archive goes back to 2007 — 'All time' really is all time.
dateFrom	string	YYYY-MM-DD. Only used when Date range = Custom.
dateTo	string	YYYY-MM-DD. Only used when Date range = Custom. Leave empty for 'today'.
feed	string	Feed mode: which live list to pull.
includeComments	boolean	Feed mode: also walk each story's comment tree into the row (slower).
commentDepth	integer	Feed mode, with comments on: how deep to walk each thread (1-5).
maxCommentsPerStory	integer	Feed mode, with comments on: cap per story (1-500).
maxResults	integer	Hard cap on dataset rows. Set 0 for unlimited (the sliding-window search really can walk the whole archive).

📤 Output

One row per result, saved to the dataset. Every row carries scrapedAt. Lookups that cannot be completed are reported in the run log rather than silently dropped.

Field	Description
type	Type
threadId	Thread Id
threadTitle	Thread Title
company	Company
headline	Headline
roleLine	Role Line
remote	Remote
urls	Urls
author	Author
hnUrl	Hn Url
createdAt	Created At
text	Text
fetchedAt	Fetched At

💼 Use cases

1. Launch monitoring — track HN discussion of a product. Input: product keywords. Output: items + points + comments. Use: a launch dashboard.

2. Hiring signals — read "Who is hiring" threads. Input: keywords. Output: items + text. Use: a hiring list.

3. Tech trends — spot rising topics on HN. Input: topic keywords. Output: items over time. Use: a trend report.

🔗 Integration

JavaScript / Node.js

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_TOKEN' });
const run = await client.actor('foxlabs/hackernews-intelligence').call({"mode":"who_is_hiring","maxResults":1000});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items[0]);

Python

from apify_client import ApifyClient
client = ApifyClient('YOUR_TOKEN')
run = client.actor('foxlabs/hackernews-intelligence').call(run_input={"mode":"who_is_hiring","maxResults":1000})
for item in client.dataset(run['defaultDatasetId']).iterate_items():
    print(item)

Automation (n8n / Zapier / Make): schedule or webhook → HTTP request to the actor API with your input → handle the JSON dataset → push to a sheet, CRM or dashboard.

📊 Pricing

Pay-per-event: per delivered record. Empty or failed lookups are never billed. View current pricing.

❓ FAQ

Do I need an account, login or API key? No. This reads public Hacker News posts and comments.

What do I search by? Keywords or topics.

How current is the data? Every run queries the source live, so results are as fresh as the registry.

What does each row cover? One HN item: title, author, points, comment count, URL and text where present.

Can I export to CSV / Excel / JSON? Yes — directly from the Apify dataset.

🐛 Troubleshooting

• Fewer rows than expected — raise maxResults, or refine the input.
• A name returns an unexpected entity — it matched a similar registered name; search the exact registry ID.
• No rows for a name — try the entity’s exact legal name or its registry ID.

⚖️ Is it legal to scrape this data?

This actor reads public Hacker News posts and comments. Results can still contain personal data (e.g. a person’s name); personal data is protected by the GDPR and similar laws, so only process it with a legitimate basis. See Apify’s blog post on the legality of web scraping.

🤝 Support & contact

• 🌐 Website: data.foxlabs.com.tr
• 📧 Email: info@foxlabs.com.tr
• 🐛 Issues: open a ticket in the Actor’s Issues tab
• 🧰 More clean B2B data actors: Fox Labs on Apify

Changelog

0.2.10 — 2026-09-20 — README examples corrected against the real input schema

• The README's code examples did not match this Actor. They used queries and maxResultsPerQuery — keys that do not exist in this Actor's input schema — with a placeholder value, and the input table listed those same phantom fields. Anyone who copied the AI-agent, cURL, JavaScript or Python example got a failing run. Every example now uses the real schema and matches the Console prefill: {"mode":"who_is_hiring","maxResults":1000}
• The input table is regenerated from input_schema.json, so it lists the fields the Actor actually accepts.
• Removed claims carried over from the same generator template where present: "formation / status monitoring", "a canonical registry record for KYB and due diligence", "every row carries query", and industry described as a NACE code.
• No code, output field or pricing change.

0.2 — 2026-09-07

• Dropped empty-promise columns. Removed emails — public Hacker News posts and comments does not carry them, so they were shipped as always-null columns. Only fields this source actually fills are now emitted.
• Enabled AI-agent payments (x402) + rebuilt the README to the full standard (What-is / when, AI-agents + x402 agentic payments + MCP, Overview, Features, Use cases, Integration, FAQ, Troubleshooting, Support & contact).

0.0

• Initial release: data from public Hacker News posts and comments by name or registry ID.