Pricing

Rating

Developer

Actor stats

Categories

Share

🚀 ProductHunt Launches & Makers Scraper

Extract every public field from any Product Hunt product page — launches, makers, votes, reviews, ratings, screenshots, topics — using just a slug, a URL, a topic page, or a daily leaderboard date. No API key required.

⭐ What You Get

For each product:

• Identity — name, slug, product URL, website URL
• Visuals — thumbnail + all screenshots (high-res, imgix CDN URLs)
• Engagement — upvote count, comment count, aggregate rating (1–5) with rating count
• Categorization — Product Hunt topics (Productivity, AI, Developer Tools, etc.) + application category
• Launch metadata — date published, date last modified
• Makers — name, avatar, profile URL for each founder/maker
• Reviews — rating, review body, author name+profile, date, for each review
• Operating system support tag (when set)

Everything is JSON-LD parsed + Apollo-state extracted — exactly what Product Hunt serves to Google.

🎯 Use Cases

• Startup intelligence — track daily launches, identify trending products in your space
• VC sourcing — find founders and their products before they break out
• Recruiter sourcing — identify makers of top-rated products by category
• Competitor monitoring — watch your competitors' launch metrics over time
• Tech newsletter — daily/weekly digest of top launches with rich metadata
• Market research — survey an entire topic (e.g., all artificial-intelligence products)

🛠️ Input

You can mix and match four ways to point the scraper at products. Provide one or more:

📤 Example Output

{
"slug":"linear",
"productUrl":"https://www.producthunt.com/products/linear",
"name":"Linear",
"tagline":"The issue tracking tool you'll enjoy using",
"websiteUrl":"https://linear.app",
"image":"https://ph-files.imgix.net/9d9aa008-....png",
"screenshots":["https://ph-files.imgix.net/35d1d856....png","..."],
"applicationCategory":"Hiring",
"datePublished":"2019-10-30T16:22:48-07:00",
"dateModified":"2026-05-18T09:02:38-07:00",
"aggregateRating":{"ratingValue":4.91,"ratingCount":395,"bestRating":5,"worstRating":1},
"votesCount":29,
"commentsCount":38,
"topics":[
{"slug":"productivity","name":"Productivity"},
{"slug":"developer-tools","name":"Developer Tools"}
],
"makers":[
{"name":"Karri Saarinen","image":"https://ph-avatars.imgix.net/508/....jpeg","profile":"https://www.producthunt.com/@karrisaarinen"}
],
"reviews":[
{
"rating":5,
"body":"Linear has completely changed how our team tracks work...",
"author":"Jane Doe",
"authorProfile":"https://www.producthunt.com/@janedoe",
"datePublished":"2025-08-12T..."
}
],
"scrapedAt":"2026-05-18T16:00:00.000Z"
}

⚡ How It Works

1. Discovery phase — for each startUrl, topicSlug, or leaderboardDate, the scraper fetches the page and harvests every /products/<slug> link.
2. Detail phase — for each unique slug, it fetches /products/<slug> and parses three JSON-LD blocks (BreadcrumbList, WebApplication/Product, Reviews) plus inline Apollo state for vote/comment counts, topics, and makers.
3. Output — one normalized record per product, pushed to the dataset as it's scraped.

No login, no API key, no JavaScript rendering — pure HTTP + JSON-LD.

💡 Tips

• Combine topicSlugs + leaderboardDates for the widest coverage.
• For a single competitor lookup, pass one productSlugs entry and set maxRecords: 1.
• If you need historical leaderboards, loop multiple leaderboardDates — each gives ~18 products.
• Default behavior with empty input scrapes Notion, Linear, and Vercel as a demo.

📊 Limits & Behavior

• maxRecords defaults to 100 to keep runs cheap and predictable.
• Set to 0 for unlimited (but you'll hit Product Hunt's rate-limiting around 200 req/min).
• The scraper exits with FAILED status if no targets are provided and no demo defaults match.

🛒 Related Scrapers

Looking for more discovery data?

• Y Combinator Companies Scraper — every YC company, batch, sector
• BuiltIn Tech Companies + Tech Stack Scraper — tech companies + their full stack
• H1B Visa Database Scraper — visa sponsors + salary data

Built with ❤️ for makers, VCs, and tech intel teams.