Can I get details of a product in the stack?

Yes. Pass its alias to the Product Hunt product source.

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 Stacks API and MCP — Products a User Runs on

Send a username or profile link and get the products in that user's stack: name, tagline, rating, review count, link and, where given, who recommended each product and when it was added. Set max_items to cap the list (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: products in the user's stack, with rating, review count and who recommended them
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	Product slug.
`machine.items[].name`	string	Product name.
`machine.items[].url`	string	Link to the product page.
`machine.items[].alias`	string	The product slug.
`machine.items[].product_id`	string	Numeric product id.
`machine.items[].tagline`	string	One-line tagline.
`machine.items[].rating`	number	Average review rating.
`machine.items[].review_count`	null	Empty in the sample; the number of reviews when given.
`machine.items[].post_count`	null	Empty in the sample.
`machine.items[].image`	string	Logo image link.
`machine.items[].categories[]`	array	Categories; empty in the sample.
`machine.items[].is_no_longer_online`	boolean	Whether the platform marks the product as no longer online.
`machine.items[].added_at`	null	Empty in the sample; when the product was added to the stack, if given.
`machine.items[].referrer`	null	Empty in the sample; who recommended the product, if given.

Response

Example response

A real response, as returned.

{
  "session_id": "11111111-1111-1111-1111-111111111111",
  "kind": "producthunt_users_stacks",
  "user": "kevin",
  "max_items": 2,
  "start_page": 1,
  "partial": false,
  "human": "# Product Hunt — user stacks\n\n- **User:** kevin\n- **Results:** 2\n- **Proxy traffic:** 276.6 KB",
  "machine": {
    "total_items": 2,
    "first_item": {
      "id": "gpt-4-openai",
      "name": "GPT-4o",
      "url": "https://www.producthunt.com/products/gpt-4-openai",
      "alias": "gpt-4-openai",
      "product_id": "113179",
      "tagline": "Fast, intelligent, flexible GPT model",
      "rating": 4.83,
      "review_count": null,
      "post_count": null,
      "image": "https://ph-files.imgix.net/da10f845-57e4-4fa9-8856-0cb9275daecf.png?auto=format&fit=crop&w=128&h=128",
      "categories": [],
      "is_no_longer_online": false,
      "added_at": null,
      "referrer": null
    },
    "items": [
      {
        "id": "gpt-4-openai",
        "name": "GPT-4o",
        "url": "https://www.producthunt.com/products/gpt-4-openai",
        "alias": "gpt-4-openai",
        "product_id": "113179",
        "tagline": "Fast, intelligent, flexible GPT model",
        "rating": 4.83,
        "review_count": null,
        "post_count": null,
        "image": "https://ph-files.imgix.net/da10f845-57e4-4fa9-8856-0cb9275daecf.png?auto=format&fit=crop&w=128&h=128",
        "categories": [],
        "is_no_longer_online": false,
        "added_at": null,
        "referrer": null
      },
      {
        "id": "spotify",
        "name": "Spotify",
        "url": "https://www.producthunt.com/products/spotify",
        "alias": "spotify",
        "product_id": "97236",
        "tagline": "Stream music and podcasts",
        "rating": 4.67,
        "review_count": null,
        "post_count": null,
        "image": "https://ph-files.imgix.net/aa6e3930-dec2-4d85-af41-d39f120e7539.jpeg?auto=format&fit=crop&w=128&h=128",
        "categories": [],
        "is_no_longer_online": false,
        "added_at": null,
        "referrer": null
      }
    ],
    "total_found": null,
    "page_count": 1,
    "blocked": false,
    "proxy_traffic_bytes": 283265
  },
  "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-stacks \
  -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.

Tool adoption

See which tools a well-known maker or investor runs on.

Competitive intelligence

Check whether a target account's team lists your product or a rival's.

Integration planning

Find which products show up together in stacks and plan integrations around them.

Outreach context

Reference a tool someone uses when you contact them about it.

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

—A stack is what a person chose to list on their profile; it is not a record of what they actually use.
—Several fields, including review count, added date and referrer, were null in the sample.
—This source returns a person's public list. Use it for product research, not to profile the individual.

FAQ

Questions, answered

There is a referrer field for it, but it was null in the sample, so it is filled only when the platform shows one.

Related sources

Product Hunt user

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

Product Hunt user collections

Collections a user has made.

Product Hunt product

Full profile of one product: rating, followers, categories, makers and similar products.

All startup & funding data

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

Try product hunt user stacks on your own data

One request format across every source in the catalog.

Get started