Product Hunt Scraper: Launches, Makers, Upvotes, Comments

From The Mine Works, makers of Threads Scraper and B2B Leads Finder, with over 245,000 runs across 280+ public actors.

Last verified 29 Oct 2026: a live test run on Apify returned 17 launches in 13 seconds.

Why choose this actor?

• Every launch of any day, week or month, with the people behind it. Give a date range and get each leaderboard as Product Hunt ranks it: our final test read the daily leaderboards of 1, 2 and 3 October 2026 and returned all 98 featured launches in 52 seconds, every one with its website, description, hunter and topics, and 93% with a makers list (the rest list no maker). No API token to apply for, no login, no cookies.
• Old launches get full details too. Product Hunt's product page only spotlights a product's recent launches, so a scraper that reads that page alone loses the makers of older ones. This actor asks for those launches one by one: in a test on Cursor's 11 launches back to 2025, 11 of 11 came back with makers, hunter, link and description.
• Pay only for new launches on a schedule. Turn on onlyNewItems and each run skips launches an earlier run delivered. In our test on the 37 featured launches of 4 October 2026, run one delivered the top 20, run two the other 17, and run three found 0 new launches and charged 0. A launch found twice in one run is delivered and charged once.

Part of The Mine Works Marketing, SEO and reviews family: Facebook Ad Library Scraper, Google Ads Transparency Scraper, Similarweb Scraper, Google News Scraper, Trustpilot Reviews Scraper, Google Trends Scraper.

Guide and FAQs: Product Hunt Scraper on themineworks.com.

Try it in one minute

Paste this into the input (JSON view) and press Start. It returns the top 20 launches of 4 October 2026 with makers, hunter, website and description, in about 35 seconds:

{
  "mode": "leaderboard",
  "startDate": "2026-10-04",
  "maxItems": 20
}

mode picks the source. leaderboard reads the daily, weekly or monthly leaderboard (period) for every date from startDate to endDate, as 2026-10-04, today, yesterday or 7 days ago. topics takes topic slugs or links (developer-tools, https://www.producthunt.com/topics/productivity). products takes product links (https://www.producthunt.com/products/notion), launch links (https://www.producthunt.com/posts/cursor-1-7) or bare product slugs. comments takes launch links or product links (the product's latest launch).

Apify's free plan includes $5 of credit every month, which covers about 3,200 results at this actor's price.

Copy to your AI assistant

themineworks/product-hunt-scraper on Apify. Scrapes Product Hunt launches from daily, weekly or monthly leaderboards over a date range, from topics, or from product and launch links, one row per launch with name, tagline, upvotes, comments count, daily, weekly and monthly rank, launch date, topics, thumbnail, product page, and (details on) makers and hunter with profile links, the launch's website, description, pricing and gallery; comments mode returns one row per comment and reply. Call ApifyClient("TOKEN").actor("themineworks/product-hunt-scraper").call(run_input={"mode": "leaderboard", "period": "daily", "startDate": "2026-10-01", "endDate": "2026-10-03", "maxItems": 50}), then client.dataset(run["defaultDatasetId"]).list_items().items. Required: none (default: yesterday's daily leaderboard). Optional: mode ("leaderboard", "topics", "products", "comments"), period ("daily", "weekly", "monthly"), startDate and endDate ("YYYY-MM-DD", "today", "yesterday", "N days ago"), featuredOnly (default true), topics (list of slugs or links), topicOrder ("newest" or "best"), productUrls (product or launch links), launchUrls (for comments), maxItems (rows per day, week, month, topic, product or launch, 20 to 5000, default 100), includeDetails (default true), onlyNewItems (default false). Full spec: GET https://api.apify.com/v2/acts/themineworks~product-hunt-scraper/builds/default (Bearer TOKEN), which returns inputSchema and readme. Token: https://console.apify.com/account/integrations?fpr=ymnoit&utm_source=apify-readme&utm_medium=referral

Key features

• Four sources in one actor: daily, weekly and monthly leaderboards for any range of dates back to November 2013 (up to 400 periods per run), topics, product and launch links, and the comments of any launch.
• 40 fields per launch row: id, name, tagline, launch link, product id, name, slug and page, website and its domain, Product Hunt's visit link, upvotes now and at the end of launch day, comments count, daily, weekly and monthly rank, launch date and time, featured flag, launch number, topics, badges such as "#1 Product of the Day", makers, hunter, thumbnail, full description, pricing label and gallery.
• Featured or every launch: the leaderboard shows featured launches by default (26 to 39 a day in early October 2026); switch featuredOnly off to get every launch of the period. Our weekly test returned 300 launches of one week in 40 seconds.
• Topics with product facts: topic rows add the product's review rating, review count, followers, number of launches and categories, newest launch first or best rated first.
• Comments as rows: one row per comment and per reply, with the author as shown, text, upvotes, time, a maker badge, the parent comment and a link. 60 comments of two launches took 15 seconds.
• A run summary you can audit: the OUTPUT record lists each source's status, rows delivered, pages read, requests by type with their success rate, and how many IPs the site let through.

How to use it

Basic: yesterday's top launches

With no input at all the actor reads yesterday's daily leaderboard (Product Hunt days run on Pacific time):

{
  "mode": "leaderboard",
  "startDate": "yesterday",
  "maxItems": 50
}

Several days at once

Every day from startDate to endDate is its own source of up to maxItems launches. This is our final test: the 98 featured launches of three days in 52 seconds, all with details.

{
  "mode": "leaderboard",
  "period": "daily",
  "startDate": "2026-10-01",
  "endDate": "2026-10-03",
  "maxItems": 50
}

Job: daily launch alerts for a newsletter or a Slack channel

Read yesterday's featured launches every morning and pay only for launches you have not received before. Save this as a task and add a daily schedule (for example 09:00 UTC, after the Pacific day has closed):

{
  "mode": "leaderboard",
  "startDate": "yesterday",
  "maxItems": 100,
  "onlyNewItems": true
}

Job: a month of makers for outreach or research

The monthly leaderboard ranks a whole month. Each row carries the makers and the hunter with their Product Hunt profile links as shown on the launch, and the launch's website, so you can see who built what:

{
  "mode": "leaderboard",
  "period": "monthly",
  "startDate": "2026-09-01",
  "maxItems": 500
}

Job: every launch of a week, fast

Switch featuredOnly off for every launch of the period, featured or not, and switch includeDetails off when names, taglines, upvotes, ranks and topics are enough. Our test returned 300 launches of week 40 of 2026 in 40 seconds with 19 requests:

{
  "mode": "leaderboard",
  "period": "weekly",
  "startDate": "2026-09-28",
  "featuredOnly": false,
  "includeDetails": false,
  "maxItems": 300
}

Job: watch a topic or a set of competitors

Topics give the products in each topic with their latest launch, newest launch first or best rated first. Product links give every launch a product has made, newest first:

{
  "mode": "topics",
  "topics": ["developer-tools", "https://www.producthunt.com/topics/artificial-intelligence"],
  "topicOrder": "newest",
  "maxItems": 20
}

{
  "mode": "products",
  "productUrls": ["https://www.producthunt.com/products/cursor", "spira-ai"],
  "maxItems": 50
}

Job: read what people said about a launch

One row per comment and reply, with the author as shown, a maker badge and upvotes. 60 comments of these two launches took 15 seconds:

{
  "mode": "comments",
  "launchUrls": ["https://www.producthunt.com/posts/cursor-1-7", "https://www.producthunt.com/products/spira-ai"],
  "maxItems": 100
}

Input parameters

Parameter	Type	Default	What it does
mode	string	leaderboard	leaderboard, topics, products or comments. Each mode reads only its own fields below.
period	string	daily	Leaderboards: daily, weekly (Product Hunt's Monday to Sunday weeks) or monthly.
startDate	string	yesterday	Leaderboards: first date, as 2026-10-01, today, yesterday or 7 days ago. Pacific time.
endDate	string	same as startDate	Leaderboards: last date, included. Up to 400 days, weeks or months per run.
featuredOnly	boolean	true	Leaderboards: featured launches only, as Product Hunt shows by default. Off adds every launch of the period.
topics	array of strings	empty	Topics mode: topic slugs or links, for example developer-tools.
topicOrder	string	newest	Topics mode: newest (latest launch first) or best (best rated first).
productUrls	array of strings	empty	Products mode: product links, launch links (/posts/<launch> or /products/<product>?launch=<launch>) or product slugs.
launchUrls	array of strings	empty	Comments mode: launch links, or product links for the product's latest launch.
maxItems	integer	100	Most rows for each source (each day, week, month, topic, product or launch), 20 to 5,000. Also the most you pay for per source.
includeDetails	boolean	true	Adds makers, hunter, website, description, every topic, pricing, gallery and badges. One more request per launch. Not used in comments mode.
onlyNewItems	boolean	false	Skips launches (or comments) an earlier run of this actor in your account already delivered. For schedules.

What data do you get?

Launch rows (type: "launch"), from leaderboards, topics and product links:

• The launch: launch_id, name, tagline, slug, url (the launch on Product Hunt), launch_date (Pacific day), launched_at, featured, launch_number, thumbnail_url.
• Numbers: upvotes, launch_day_upvotes, comments_count, daily_rank, weekly_rank, monthly_rank, badges.
• The product: product_id, product_name, product_slug, product_url, website, website_domain, redirect_url (Product Hunt's visit link).
• People, as shown on the launch: makers (name, username, profile_url, headline), maker_names, hunter_name, hunter_username, hunter_url.
• Content: topics, topic_slugs, description, pricing (free, free_options or payment_required), media (gallery images and videos).
• Topic rows also get: product_rating, product_reviews_count, product_followers, product_launches_count, product_categories, topic.
• Where it came from: source (for example daily 2026-10-02), source_type, position, details (read, off, or not read with the reason), scraped_at.

Comment rows (type: "comment"): comment_id, parent_comment_id, thread_id, depth (0 for a top comment), body as plain text, author_name, author_username, author_url, author_headline, is_maker, is_hunter, comment_badges, upvotes, replies_count, is_pinned, created_at, comment_url, and the launch: launch_id, launch_name, launch_slug, launch_url, product_slug.

How often each field was filled in our final test runs:

Field	Filled	Why not always
launch_id, name, tagline, url, product_slug, upvotes, comments_count, daily_rank, weekly_rank, monthly_rank, launch_date, topics, thumbnail_url	100% of 98 leaderboard rows
website, description, hunter_name, hunter_url, launch_number, product_name	100% of 98	With includeDetails on (the default).
makers, maker_names	93% of 98	Some launches list no maker, only a hunter.
pricing	98% of 98	A few launches have no pricing label.
badges	15% of 98	Only the top 5 of a day, week or month get a badge.
featured	100% of 300	In the every launch test, 230 featured and 70 not.
author_headline	52% of 60 comments	Only authors with a headline or byline.

Stable fields for automations

These fields were present in every launch row of our final runs, with and without details, and their names will not change:

Field	Meaning
type	launch (or comment in comments mode)
launch_id	Product Hunt launch id, stable across runs
name	Launch name
tagline	Launch tagline
slug	Launch slug, as in producthunt.com/posts/<slug>
url	The launch on Product Hunt
product_slug	Product slug
product_url	Product page on Product Hunt
upvotes	Upvotes when the row was read
comments_count	Comments on the launch
launch_date	Launch day, YYYY-MM-DD, Pacific time
topics	Topic names
source	The day, week, month, topic, product or launch the row came from
details	read, off, or not read with the reason
scraped_at	When the row was read, ISO 8601 UTC

Output examples

A launch with details (products mode, a launch link, trimmed):

{
  "type": "launch",
  "launch_id": "1021616",
  "name": "Cursor 1.7",
  "tagline": "Agent autocomplete, hooks, and team rules",
  "url": "https://www.producthunt.com/products/cursor?launch=cursor-1-7",
  "product_name": "Cursor",
  "product_url": "https://www.producthunt.com/products/cursor",
  "website": "https://cursor.com/changelog/1-7",
  "website_domain": "cursor.com",
  "upvotes": 388,
  "launch_day_upvotes": 283,
  "comments_count": 13,
  "daily_rank": 4,
  "weekly_rank": 18,
  "monthly_rank": 67,
  "launch_date": "2025-10-01",
  "featured": true,
  "launch_number": 5,
  "topics": ["Developer Tools"],
  "makers": [
    { "name": "Ben Lang", "username": "benln", "profile_url": "https://www.producthunt.com/@benln", "headline": "Cursor" },
    { "name": "Jon Kaplan", "username": "jonk1", "profile_url": "https://www.producthunt.com/@jonk1", "headline": "Product Eng at Cursor" }
  ],
  "hunter_name": "Ben Lang",
  "hunter_url": "https://www.producthunt.com/@benln",
  "description": "Cursor 1.7 is here! Introducing autocomplete for agent, hooks, team rules, ability to share prompts with deeplinks, and more. Look forward to hearing what you think!",
  "source": "launch cursor-1-7",
  "details": "read"
}

A launch from a weekly leaderboard with every launch and details off (trimmed):

{
  "type": "launch",
  "launch_id": "1263552",
  "name": "Cura",
  "tagline": "Your AI travel agent that plans, books, and adapts",
  "url": "https://www.producthunt.com/products/cura-3?launch=cura-4",
  "product_url": "https://www.producthunt.com/products/cura-3",
  "upvotes": 98,
  "comments_count": 34,
  "daily_rank": 40,
  "weekly_rank": 231,
  "launch_date": "2026-10-01",
  "featured": false,
  "topics": ["Productivity", "Travel", "Artificial Intelligence"],
  "source": "weekly 2026 week 40",
  "position": 231,
  "details": "off"
}

A topic row, with the product facts topics add (trimmed):

{
  "type": "launch",
  "name": "Claude Sonnet 5.5",
  "tagline": "Anthropic's second model in the Claude 5.5 family",
  "product_name": "Claude by Anthropic",
  "website": "https://www.anthropic.com/claude-sonnet-5-5",
  "upvotes": 282,
  "daily_rank": 4,
  "launch_date": "2026-09-29",
  "launch_number": 44,
  "badges": ["#4 Product of the Day (2026-09-29)"],
  "hunter_name": "Rohan Chaubey",
  "pricing": "free_options",
  "product_rating": 4.96,
  "product_reviews_count": 1021,
  "product_followers": 87864,
  "product_categories": ["LLMs", "AI Chatbots"],
  "topic": "Productivity",
  "source": "topic productivity"
}

A comment row (trimmed):

{
  "type": "comment",
  "comment_id": "4902860",
  "depth": 0,
  "body": "Excited to launch this!! Can't wait to see what everyone builds :)",
  "author_name": "Jon Kaplan",
  "author_url": "https://www.producthunt.com/@jonk1",
  "author_headline": "Cursor",
  "is_maker": true,
  "upvotes": 9,
  "created_at": "2025-09-30T12:37:33-07:00",
  "comment_url": "https://www.producthunt.com/products/cursor?comment=4902860",
  "launch_name": "Cursor 1.7",
  "launch_url": "https://www.producthunt.com/products/cursor?launch=cursor-1-7"
}

Pricing

Pay per event: you pay for the rows you receive, plus a flat $0.005 per run, whatever memory you choose.

Event	When it is charged	Free plan	Bronze (Starter)	Silver (Scale)	Gold (Business)
item-scraped	Once per launch or comment row stored in your dataset	$1.49 per 1,000	$1.29 per 1,000	$1.09 per 1,000	$0.89 per 1,000
run-start	Once per run, when it starts	$0.005	$0.005	$0.005	$0.005

The price per single row is the price per 1,000 divided by 1,000. A launch with makers, hunter, website and description costs the same as one without.

Never charged:

• requests Product Hunt refused, and sources the run could not read;
• days, topics or products with no launches, and links that lead nowhere;
• a launch already delivered earlier in the same run (for example a launch that is in two topics);
• with onlyNewItems, launches or comments an earlier run already delivered;
• the info row at the end of a run;
• anything past your "Max cost per run": the actor stops delivering when your limit is reached instead of sending rows for free.

FAQ

What exactly does this actor read?

The public pages of producthunt.com, the site where new tech products launch every day, through the same data service the Product Hunt website calls for every visitor: leaderboards, topic pages, product pages, launch pages and their comments. Nothing behind a login is read, and you do not need a Product Hunt API token.

How many launches can I get?

A day has 26 to 39 featured launches in early October 2026 and often 300 or more launches in all. maxItems caps each source (each day, week, month, topic, product or launch) at 20 to 5,000 rows, and one run can cover up to 400 days, weeks or months. Leaderboards go back to Product Hunt's first day in November 2013.

How long does a run take?

Leaderboards come 20 launches a request, and details take one more request per launch, eight at a time. Our final tests: 98 launches of three days with details in 52 seconds, 300 launches of one week without details in 38 seconds, 40 launches of two monthly leaderboards with details in 37 seconds, and 60 comments in 15 seconds.

How fresh is the data?

Every run reads Product Hunt live. Upvotes and comment counts are the numbers at the moment of the run; launch_day_upvotes keeps the count at the end of launch day.

Why do some launches have no makers?

Product Hunt lists makers only when the launch team added them. In our three day test, 91 of 98 launches had at least one maker; the other 7 show only the hunter, exactly as on the site.

What are featured launches?

Product Hunt's editors feature a selection of each day's launches; the leaderboard shows those by default. Turn featuredOnly off to get every launch of the day, week or month, and read the featured field on each row.

Do I need an account, cookies or an API token?

No. The actor reads what any logged out visitor sees, with no login, no cookies and no token from you.

Do I need a proxy?

No. The actor brings its own: it uses Apify's datacenter proxy, keeps the addresses Product Hunt lets through and drops the ones it refuses. You pay nothing extra for it.

What happens with a wrong link or slug?

It is listed in the run's OUTPUT record with the status not_found and is not charged; the rest of the run carries on. A link that is not a Product Hunt link is reported in the log and skipped.

Can I run it on a schedule and get only new launches?

Yes. Use startDate: "yesterday", turn on onlyNewItems, save the input as a task and add a daily schedule. Each run skips launches earlier runs delivered: in our test the third run of the same day found 0 new launches and charged 0.

Which formats can I download?

JSON, CSV, Excel, XML, RSS and an HTML table, from the run's dataset in Console or through the API. Lists such as makers and topics become columns in CSV and Excel.

Can I use it from Claude, ChatGPT or Cursor (MCP)?

• Connector URL: https://mcp.apify.com/?tools=themineworks/product-hunt-scraper
• Claude: Settings > Connectors > Add custom connector, paste the URL, sign in with Apify.
• ChatGPT: developer mode, add an MCP connector with the URL, sign in with Apify.
• Cursor or VS Code: add it as an HTTP MCP server with that URL.
• Claude Code: claude mcp add -t http product-hunt-scraper "https://mcp.apify.com/?tools=themineworks/product-hunt-scraper"

Is it legal to scrape Product Hunt?

The actor reads only what Product Hunt shows publicly to anyone without signing in. Makers, hunters and commenters appear with the name, username, profile link and headline they chose to show; the actor collects no email addresses or phone numbers. You are responsible for how you use the data, for Product Hunt's terms, and for data protection law such as GDPR and CCPA, which matters most if you contact people. If in doubt, ask a lawyer about your use case.

Integrations

• Google Sheets: send each run's rows to a sheet with Apify's Google Sheets integration, or import the CSV link of the dataset.
• Make, Zapier and n8n: start the actor and read its dataset with the Apify apps and nodes, for example "yesterday's top 10 launches to Slack every morning".
• Webhooks: have Apify call your URL when a run succeeds, then fetch the dataset.
• API and SDKs: run it from Python or JavaScript with the Apify client, or with a plain HTTP call (see "Copy to your AI assistant" above).
• MCP clients: Claude, ChatGPT, Cursor and VS Code can run it as a tool through the connector URL in the FAQ.

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Support

A launch, topic or day that should return rows and does not? Open an issue in the Issues tab with the input and the run ID, and we will look at it. For another source or a field you need, email dmineworks@gmail.com.

Pick a day, a week, a month, a topic or a product, and get every Product Hunt launch back as a clean row with its upvotes, rank, website and the people who made it.