Hacker News Scraper — Posts, Points, Comment Count

Search Hacker News for any keyword: stories and comments with title, URL, author, points, comment count and date. Reads the official Algolia HN API, so it never breaks on layout changes. Export to JSON, CSV or Excel, or call it as an API. For tech research and brand mentions.

Price: $1 per 1,000 stories and comments ($0.001 per story or comment). The first 10 results of every run are free.

100% first-party. Reads the official Hacker News (Algolia) search API directly — no third-party scraper in the middle, nothing that can break on a layout change. $1 per 1,000 results, first 10 of every run free.

Free tier — 10 results free on every run

The first 10 results of every run are free, on every run you ever make — not a one-off trial. Run it on your own subjects and see the real output before you are billed for a single result.

One guard: the free allowance never covers more than half of a run, so a run returning 6 results gets 3 free. That keeps the offer sustainable.

What it does

Run it once and get the full, current data as clean rows you can export to JSON, CSV or Excel, or pull through the API. Need only fresh data? Turn on monitorEnabled and schedule it: every later run returns only what is new or changed since the previous one, so you never re-download or re-pay for the same rows.

Why this scraper

1. Try before you pay. The first 10 results of every run are free, on every run.
2. Pay only for data delivered. Failed sources and failed inputs are never billed.
3. Hard cost cap. Set maxTotalChargeUsd and a run can never cost more than you allow.
4. Only-new mode. With monitorEnabled on a schedule, you get just the new or changed rows, plus a spike signal when volume suddenly jumps.
5. Clean, normalized rows with the same field names every run, plus a RUN_SUMMARY.json — ready for spreadsheets, databases, n8n/Make/Zapier and AI agents (MCP).

Example input

{
  "keywords": [
    "your product",
    "competitor name"
  ],
  "maxTotalChargeUsd": 1.0
}

This returns the full current data right away. To receive only what is new on a schedule, add "monitorEnabled": true: the first monitored run stores a free baseline, later runs return only new or changed rows. Pin a monitorId to keep separate targets from sharing state.

All input fields

Beyond keywords, these fields are optional:

Field	What it does
sections	Whole sections: front, newest, ask, show, jobs, best. Works with or without keywords.
maxStories	Results per keyword or section, 1 to 10,000. Default 100.
contentType	all (default), stories or comments.
sortBy	date (default) or popularity (at most 1,000 results).
dateFrom / dateTo	Date range, YYYY-MM-DD.
minPoints / minComments	Keep only stories above these numbers.

Every row also has type (story, comment or job), section, domain and rank_in_list.

Output

Each row is a normalized record: record_id, query_id, title, url, author, published_at, score, text. A RUN_SUMMARY.json accompanies every run with the aggregated signal (counts, velocity spikes, trend).

text is an empty string, not missing data, for link-only submissions (a story that just posts a URL with no self-text) — this is what Hacker News itself stores for that story, not a scraping gap. Stories with real self-text (Ask HN, Show HN, most comments) return it in full.

Each row also keeps the fields the source itself returns (for example extra details, counts and links), so you get everything the source shows plus the normalized columns above.

How you're charged

• Story or comment — $0.001 per story or comment ($1 per 1,000), billed for each story or comment delivered to your dataset. With scheduled monitoring on, only stories and comments that are new since the last check are delivered and billed.
• Scheduled monitoring check ($0.002) — only when you turn on scheduled monitoring (monitorEnabled), once per target per run, and only when the source responded. One-off runs never pay it: you pay only per result.
• A quiet monitored run bills only the source check ($0.002), never the result price.

Related tools

• Looking for Q&A-style developer discussion instead of link/comment threads? → Stack Overflow Scraper - Questions, Answers, Vote Count

How to use it in 3 steps

1. Click Try for free and fill in Search keywords (keywords).
2. Optional: adjust the other fields; every one has a description and a sensible default.
3. Click Start and download the results as JSON, CSV or Excel, or read them from the API.

Use cases

• Tech research
• Brand mentions

Use it from code (API)

Every Apify Actor is an API. Start a run and read the results with one call.

Python

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("om_kh/hacker-news-scraper").call(run_input={"keywords": ["your product", "competitor name"]})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('om_kh/hacker-news-scraper').call({
    "keywords": [
        "your product",
        "competitor name"
    ]
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

One HTTP call (cURL) — runs the Actor and returns the dataset in the same response:

curl -X POST "https://api.apify.com/v2/acts/om_kh~hacker-news-scraper/run-sync-get-dataset-items?token=<YOUR_APIFY_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"keywords": ["your product", "competitor name"]}'

Integrations: n8n, Make, Zapier, Google Sheets

• n8n — the official Apify node, operation Run Actor and get dataset, Actor om_kh/hacker-news-scraper.
• Make — Apify › Run an Actor, then Apify › Get Dataset Items.
• Zapier — Apify › Run Actor; map the dataset items into your next step.
• Google Sheets, webhooks, Slack — add an integration from the Integrations tab of this Actor.
• Schedules — run it every hour or day from Schedules in Apify Console.

Use it from an AI agent (MCP and x402)

Connect Claude Desktop, Cursor, VS Code or any MCP client to Apify's MCP server at https://mcp.apify.com and add this Actor, om_kh/hacker-news-scraper, as a tool — the agent passes the same JSON as the run input and gets the dataset back.

AI agents that pay with x402 can run it too, without an Apify account: the Actor charges only per result delivered, so an agent pays exactly for what it gets.

FAQ

Is it legal to scrape Hacker News? This Actor collects only publicly available Hacker News data and never logs in. You are responsible for how you use it; check Hacker News's terms and your local law (GDPR, CCPA) if you store personal data, and ask a lawyer if unsure.

Do I need an account, cookies or an API key? No. You only need an Apify account to run it.

What data do I get? Matching stories and comments with points, comment count, author and date. Download it as JSON, CSV, Excel, HTML or XML, or read it from the API.

Am I charged when something fails? No. An input that fails is listed with its reason in the run summary and is never charged.

Can I run it on a schedule? Yes. Create a schedule in Apify Console (hourly, daily, weekly) and connect webhooks, Google Sheets, Slack, n8n, Make or Zapier.

Can I use it from Python, JavaScript or an AI agent? Yes: see the code samples above, or connect AI agents through MCP with the hackernews_search tool.

Your feedback

Did this Actor save you time? A short review on the Reviews tab helps other people find it, and every review is read. Something missing or broken? Open an issue on the Issues tab: it is answered and fixed fast.

More Actors from the same author

• Stack Overflow Scraper - Questions, Answers, Vote Count
• Yelp Reviews Scraper - Ratings, Text, Reviewer Name
• App Store & Google Play Reviews Scraper - Ratings
• Quora Scraper - Questions, Answers, Topics by Keyword

Support

Found a bug or have a feature request? Use the Issues tab on this Actor's Apify Store page, or message the author (om_kh) directly through Apify — every report gets a reply.