How is this different from the product launches source?

That source lists all launches of one product. This one lists launches submitted by one user.

Do I pay for lookups that come back empty?

No. You are charged per result, so a request that finds nothing costs nothing. Testing this against a messy list is free to get wrong.

What does a request cost?

1 point per returned record, which is $1 per 1,000, and only records that come back are charged. Points come out of your monthly plan allowance.

Startup & Funding Data

Product Hunt User Launches API and MCP — Submitted Launches with Votes and Ranks

Send a username or profile link and get the launches that user submitted: launch name, tagline, votes, comments, daily, weekly and monthly rank, and dates. All pages are read, up to the max_items you set (up to 250).

Run it in the app Read the API docs

You send: a Product Hunt username or profile link, and how many results to return
You get back: launches the user submitted, with votes, comments, ranks and dates
Coverage: Product Hunt records with a public page.
Price: 1 point per returned record — $1 per 1,000; Billed per record actually returned, capped by max_items. A request that returns nothing costs nothing.

Comparison

Ways to get this data

Three approaches teams use today, and where each one runs into trouble.

Approach	What it takes	Cost	Trade-off
Product Hunt directly	Open the page on Product Hunt and scroll through the list	Free, and slow	Fine for one record, useless across a list, and the layout differs on every platform
Building a scraper	Write it, host it, and repair it when Product Hunt changes its pages	Engineering time	A maintenance commitment for something that isn't your product
NeuralVerge	One request, the same shape as every other source in the catalog	$1 per 1,000, misses not billed	Returns what Product Hunt publishes at request time. Other platforms are separate sources with the same request format

Response

What you get back

Every field in the example response below.

Field	Type	Description
`session_id`	string	Id of this run, for tracing.
`kind`	string	Source type of the response.
`user`	string	The username you sent.
`max_items`	number	The cap you sent on returned records.
`start_page`	number	Page the run started from.
`partial`	boolean	Whether the run stopped before reaching everything that matched.
`human`	string	Readable summary of the run.
`total_points`	number	Points charged for the run: 1 per returned record.
`machine.total_items`	number	Number of records returned in this response.
`machine.total_found`	null	Empty in the sample because the platform gave no total for this request.
`machine.page_count`	number	Pages read for the run.
`machine.first_item`	object	The first returned record, repeated from items[]. Fields below are described on items[].
`machine.blocked`	boolean	Whether the platform refused the request.
`machine.proxy_traffic_bytes`	number	Size of the data transferred for the run, in bytes.
`machine.items[].id`	string	Launch slug.
`machine.items[].name`	string	Launch name.
`machine.items[].url`	string	Link to the launch page.
`machine.items[].alias`	string	The launch slug.
`machine.items[].launch_id`	string	Numeric launch id.
`machine.items[].tagline`	string	Tagline shown on the launch.
`machine.items[].votes_count`	number	Upvotes on the launch.
`machine.items[].comments_count`	number	Comments on the launch.
`machine.items[].daily_rank`	number	Rank on the launch day.
`machine.items[].weekly_rank`	number	Rank in the launch week.
`machine.items[].monthly_rank`	number	Rank in the launch month.
`machine.items[].topics[]`	array	Topics on the launch; empty in the sample.
`machine.items[].image`	string	Launch image link.
`machine.items[].product_slug`	string	Slug of the product the launch belongs to.
`machine.items[].product_url`	string	Link to that product.
`machine.items[].featured_at`	string	Date and time the launch was featured.
`machine.items[].created_at`	string	Date and time the launch was created.

Response

Example response

A real response, as returned.

{
  "session_id": "11111111-1111-1111-1111-111111111111",
  "kind": "producthunt_users_launches",
  "user": "kevin",
  "max_items": 2,
  "start_page": 1,
  "partial": false,
  "human": "# Product Hunt — user launches\n\n- **User:** kevin\n- **Results:** 2\n- **Proxy traffic:** 17.9 KB",
  "machine": {
    "total_items": 2,
    "first_item": {
      "id": "busabase",
      "name": "Busabase",
      "url": "https://www.producthunt.com/posts/busabase",
      "alias": "busabase",
      "launch_id": "1189118",
      "tagline": "The general system of record for AI agents",
      "votes_count": 139,
      "comments_count": 32,
      "daily_rank": 2,
      "weekly_rank": 35,
      "monthly_rank": 160,
      "topics": [],
      "image": "https://ph-files.imgix.net/27868ffa-a004-487a-8861-71e60914cbd6.png?auto=format&fit=crop&w=128&h=128",
      "product_slug": "busabase",
      "product_url": "https://www.producthunt.com/products/busabase",
      "featured_at": "2026-10-09T00:01:00-07:00",
      "created_at": "2026-10-09T00:01:00-07:00"
    },
    "items": [
      {
        "id": "busabase",
        "name": "Busabase",
        "url": "https://www.producthunt.com/posts/busabase",
        "alias": "busabase",
        "launch_id": "1189118",
        "tagline": "The general system of record for AI agents",
        "votes_count": 139,
        "comments_count": 32,
        "daily_rank": 2,
        "weekly_rank": 35,
        "monthly_rank": 160,
        "topics": [],
        "image": "https://ph-files.imgix.net/27868ffa-a004-487a-8861-71e60914cbd6.png?auto=format&fit=crop&w=128&h=128",
        "product_slug": "busabase",
        "product_url": "https://www.producthunt.com/products/busabase",
        "featured_at": "2026-10-09T00:01:00-07:00",
        "created_at": "2026-10-09T00:01:00-07:00"
      },
      {
        "id": "agentsdr",
        "name": "AgentSDR",
        "url": "https://www.producthunt.com/posts/agentsdr",
        "alias": "agentsdr",
        "launch_id": "1271403",
        "tagline": "Open-source AI SDR",
        "votes_count": 83,
        "comments_count": 3,
        "daily_rank": 13,
        "weekly_rank": 89,
        "monthly_rank": 312,
        "topics": [],
        "image": "https://ph-files.imgix.net/22c24bb2-d817-473e-9676-2cc6c699c4c5.png?auto=format&fit=crop&w=128&h=128",
        "product_slug": "agentsdr",
        "product_url": "https://www.producthunt.com/products/agentsdr",
        "featured_at": "2026-10-09T00:01:00-07:00",
        "created_at": "2026-10-09T00:01:00-07:00"
      }
    ],
    "total_found": null,
    "page_count": 1,
    "blocked": false,
    "proxy_traffic_bytes": 18367
  },
  "total_points": 2
}

Integration

How to run it

The same lookup works from the app, the API, or as a tool an agent can call mid-task.

Results come back in the same envelope as every other source: a session id, a readable summary, the structured result and the points charged. max_items caps how many records are returned and billed.

curl -X POST https://api.neuralverge.ai/functions/v1/run-producthunt-users-launches \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"user":"kevin","max_items":2}'

Use cases

What teams use it for

Where this field shows up in an actual workflow.

Hunter track record

See which launches a user brought to the platform and how they ranked.

Launch discovery

Find recent launches in a user's portfolio and look each product up.

Benchmarking

Compare votes and ranks across launches to see what a typical result looks like for a submitter.

Lead lists

Collect product names and links from the launches of people active in your market.

Coverage & limits

Coverage, freshness and limits

What this source covers, how fresh it is, and where it stops.

Coverage

Product Hunt records with a public page.

Freshness

Read at request time, so the answer reflects the platform as it stands when you ask.

Handling

This source returns information Product Hunt shows publicly. Every response carries the session id you can trace.

What it will not do

—The user submitted these launches; they are not necessarily the user's own products.
—Ranks and counts are as the platform shows them at request time.
—The sample returned no total (total_found is null), and the topics list was empty.

FAQ

Questions, answered

Not necessarily. They are launches the user submitted, which can be products made by others.

Related sources

Product Hunt user

Profile of one Product Hunt user with follower and launch counts.

Product Hunt product launches

Every launch of a product with votes and ranks.

Product Hunt user upvotes

Launches a user upvoted, newest first.

All startup & funding data

Startup directories, funding databases, launch platforms and investor data.

Try product hunt user launches on your own data

One request format across every source in the catalog.

Get started