Hacker News Show HN Launch Tracker

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Track Show HN launches and turn them into structured product, startup, and developer-tool intelligence.

Generic Hacker News scrapers return posts. This Actor focuses on one high-signal workflow: monitoring products launched to the Hacker News community and extracting useful launch metadata for founders, investors, developer advocates, market researchers, and indie hackers.

Who should use this

• Founders looking for adjacent products, positioning ideas, and launch examples
• Product managers tracking new tools in AI, developer tooling, productivity, infra, and security
• VC, accelerator, and startup researchers watching early product signals
• DevRel teams looking for new developer tools, OSS projects, APIs, and CLI products
• Content and newsletter operators building a launch/trend feed

Best first run

Track recent AI-related Show HN launches:

{
"maxItems":50,
"query":"AI",
"minPoints":0,
"minComments":0,
"includeText":true
}

Leave query empty to collect the latest Show HN launches across all categories.

What it extracts

Each output row includes:

• product name
• title and Hacker News URL
• external launch URL and domain
• author
• points and comment count
• created date
• inferred category
• launch signals such as ai, openSource, github, api, cli, yc, beta, waitlist, mobile, browserExtension
• traction score
• cleaned self-post text when available

Scheduled monitoring examples

Use Apify schedules to turn this Actor into a recurring launch-intelligence feed.

Daily product launch feed

{
"maxItems":100,
"query":"",
"minPoints":0,
"minComments":0,
"includeText":false
}

Suggested schedule: daily. Sort by createdAt or tractionScore.

Weekly AI startup and devtool watch

{
"maxItems":200,
"query":"AI OR LLM OR agent",
"minPoints":3,
"minComments":1,
"includeText":true
}

Suggested schedule: weekly. Review rows where signals.ai, signals.api, signals.cli, signals.github, or signals.openSource are true.

High-signal launch research

{
"maxItems":100,
"createdAfter":"2026-01-01",
"query":"database",
"minPoints":10,
"minComments":3,
"includeText":true
}

Suggested use: find launches with real HN traction, then inspect discussion threads for user objections, praise, and feature requests.

Example input

{
"maxItems":100,
"createdAfter":"2026-01-01",
"query":"AI",
"minPoints":10,
"minComments":2,
"includeText":true
}

Leave query and createdAfter empty to get the latest Show HN launches.

Example output

{
"id":48123456,
"productName":"ExampleDB",
"title":"Show HN: ExampleDB – An embedded database for TypeScript apps",
"url":"https://example.com",
"domain":"example.com",
"hnUrl":"https://news.ycombinator.com/item?id=48123456",
"author":"founder123",
"points":84,
"commentCount":31,
"createdAt":"2026-05-30T13:20:00.000Z",
"category":"developer-tools",
"signals":{
"ai":false,
"openSource":true,
"github":true,
"api":true,
"cli":false,
"yc":false,
"beta":false,
"waitlist":false,
"mobile":false,
"browserExtension":false
},
"tractionScore":146,
"source":"hacker-news-show-hn"
}

Use cases

• Track new developer tools and indie products.
• Build a daily startup launch intelligence feed.
• Find products gaining traction in AI, infrastructure, API, database, security, or productivity.
• Monitor competitors and adjacent markets.
• Feed launches into Airtable, Notion, Google Sheets, Slack, or a research database.

Why this Actor instead of a generic HN scraper

Generic HN scrapers collect many kinds of posts. This Actor is tuned specifically for launch research:

• Only collects Show HN launches
• Extracts product names and domains
• Adds category inference for AI, developer tools, database, security, productivity, finance, mobile, and more
• Adds launch signals such as GitHub, API, CLI, YC, beta, waitlist, mobile app, browser extension, and open source
• Calculates tractionScore from HN points and comment volume
• Saves a Markdown SUMMARY with top launches, category counts, and signal counts

If you need every HN story, use a general HN scraper. If you want startup, product, and developer-tool launch intelligence, use this Actor.

Practical workflow

1. Start with the latest 50-100 Show HN launches.
2. Use query for a focused category such as AI, API, database, security, or open source.
3. Add minPoints and minComments when you only want traction.
4. Sort by tractionScore to identify launches with strong discussion.
5. Export to CSV, Google Sheets, Airtable, Notion, or your own research database.

What you can automate next

• Daily launch digest in Slack or Discord using Apify integrations
• Weekly AI/devtool research CSV for product teams or newsletters
• Competitor watchlists for specific categories
• Founder outreach lists based on product domain and HN profile
• Trend reports based on categories and signal counts

Data source

Uses the public Hacker News Algolia API. No login, cookies, proxy, or API key required.