Product Hunt Launches Scraper

Extract Product Hunt products, launches, keyword search results, maker profiles, reviews, categories, media, social links, product websites, and optional public contact emails.

Input

Choose mode first:

Mode	Uses	Ignores
url	startUrls	searchTerms
keyword	searchTerms, searchSort, searchCategories, searchCategorySlugs	startUrls

For URL mode, paste Product Hunt URLs in startUrls:

URL shape	Output
https://www.producthunt.com/	Recent product rows
/search?q={keyword}	Product rows matching the keyword
/leaderboard/daily/YYYY/M/D	Ranked product rows
/leaderboard/weekly/YYYY/WW	Ranked product rows
/leaderboard/monthly/YYYY/M	Ranked product rows
/leaderboard/yearly/YYYY	Ranked product rows
/topics/{slug}	Product rows for that topic
/collections/{slug}	Product rows from the collection
/collections	Product rows from listed collections
/products/{slug}	One product row
/@username	One maker profile row

Useful options:

Field	Description
mode	Selects URL list or keyword search
searchTerms	Keyword searches to expand into product rows
searchSort	Sort generated keyword searches by relevance, popular, or newest
searchCategories	Multi-select common Product Hunt categories for keyword searches
searchCategorySlugs	Advanced custom Product Hunt category slugs
enrichEmails	Checks product websites for public contact emails
includeReviews	Includes public Product Hunt review details where present
outputReviewsAsRows	Saves extracted reviews as separate rows
maxReviewsPerProduct	Limits reviews attached to each product
minReviewsCount	Keeps only products with at least this many reviews
minFollowersCount	Keeps only products with at least this many followers
websiteRequired	Keeps only products with an external website URL
socialLinkRequired	Keeps only products with a social or source-code URL
maxItems	Hard cap on total dataset rows
maxSearchResultsPerTerm	Search candidates scanned per keyword before filters are applied
proxy	Optional connection settings

maxItems is the only finite default cap. Leave proxy settings simple for light runs; enable proxy or choose Residential if your run sees rate limits. Datacenter or free proxy configurations can be less reliable for larger runs.

Resume & recurring updates

Two different features, both optional and off by default:

Field	Description
resumeFromRunId	Continue ONE specific interrupted run/dataset — returns and charges only rows not already collected there
incrementalMode	Recurring monitoring of the SAME search/URL set (e.g. daily). The actor remembers the previous run itself; later runs return only what changed
stateKey	Optional name for an incremental-mode monitoring campaign; auto-derived from the search/URL and filter/enrichment settings when left empty
emitUnchanged	Also return (and bill) products unchanged since the last incremental run
emitExpired	Also return (and bill) products no longer found, once a run has fully scanned the tracked search/URL set

In incremental mode, product rows carry changeType (NEW / UPDATED / UNCHANGED / REAPPEARED / EXPIRED), changedFields, firstSeenAt, and lastSeenAt. These fields are never present outside incremental mode. Only product rows are tracked for change detection — maker-profile rows and review rows (when outputReviewsAsRows is on) are never suppressed or classified; a review row is always emitted alongside its still-pushed parent product. Note that reviews[], reviewsCount, and followersCount are ordinary fields of the product record, so a genuinely new review or follower on a tracked product still marks it UPDATED — that is the product's own activity, not noise.

scrapedAt is excluded from change detection (it is generated at scrape time, not read from the page, so it always differs). votesCount and commentsCount are always null in every row — Product Hunt's vote/comment counts are per-launch, not per-product, so there is no reliable product-level number to report; this is unrelated to incremental mode and holds with it on or off.

Send results into your apps (MCP connectors)

Optionally pipe the scraped results into the apps you already use, via Model Context Protocol (MCP) connectors. This is an extra delivery step after the scrape; the Apify dataset is never changed.

What gets written to the connector: a condensed, human-readable summary of each record, not the full JSON. Each item becomes one entry with a title and its key fields flattened to plain text. The complete record always stays in the Apify dataset.

1. Authorize a connector once under Apify → Settings → Integrations (Notion, Linear, Airtable, or Apify).
2. Select it in the "Pipe results into your apps" input field. (If the picker is empty, you haven't authorized a connector yet.)
3. For Notion, also set notionParentPageUrl to the page where items should be created.

The connection is mediated by Apify's MCP proxy, so this actor never sees your third-party credentials. Leave the field empty to skip.

Output

Product rows include:

• rowType, id, slug, name, tagline, description
• canonicalUrl, sourceUrl, websiteUrl, social links, app links
• votesCount, commentsCount, followersCount, reviewsCount
• logoUrl, media[], mediaCount
• categories[]
• reviews[], reviewsExtracted, averageRating
• harvestedEmails[] when email enrichment is enabled
• searchContext with the discovery URL and result position

Maker rows include:

• rowType, id, username, name, headline, avatarUrl
• productUrls[], productsCount

Review rows, when enabled, include:

• rowType, id, productSlug, productUrl, reviewId, reviewUrl
• rating, ratingMax, reviewText
• positiveNotes[], negativeNotes[]
• authorName, authorUrl, authorImage

Notes

The Actor reads public Product Hunt pages only. Product website email discovery is best-effort: many sites do not publish email addresses, hide them behind scripts, or use forms instead.

Legal

Scrape only publicly available data and comply with Product Hunt's Terms of Service and applicable privacy laws when using personal data such as maker names or public email addresses.