Product Hunt User Upvotes API and MCP — Launches a User Upvoted
Send a username or profile link and get the launches that user upvoted, newest first: launch name, tagline, votes, comments, daily, weekly and monthly rank, and dates. The platform serves at most the latest 200 upvotes of a user, so that is the ceiling for this source however high max_items is.
- You send
- a Product Hunt username or profile link, and how many results to return
- You get back
- launches the user upvoted, newest first, 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.
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 |
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. |
Example response
A real response, as returned.
{
"session_id": "11111111-1111-1111-1111-111111111111",
"kind": "producthunt_users_upvotes",
"user": "kevin",
"max_items": 2,
"start_page": 1,
"partial": false,
"human": "# Product Hunt — user upvotes\n\n- **User:** kevin\n- **Results:** 2\n- **Proxy traffic:** 17.4 KB",
"machine": {
"total_items": 2,
"first_item": {
"id": "openseo-2",
"name": "OpenSEO",
"url": "https://www.producthunt.com/posts/openseo-2",
"alias": "openseo-2",
"launch_id": "1272262",
"tagline": "The open source Semrush alternative",
"votes_count": 354,
"comments_count": 39,
"daily_rank": 2,
"weekly_rank": 9,
"monthly_rank": 12,
"topics": [],
"image": "https://ph-files.imgix.net/2c78fe4a-262c-48b2-a376-365b77bf6eeb.png?auto=format&fit=crop&w=128&h=128",
"product_slug": "openseo",
"product_url": "https://www.producthunt.com/products/openseo",
"featured_at": "2026-10-08T00:01:00-07:00",
"created_at": "2026-10-08T00:01:00-07:00"
},
"items": [
{
"id": "openseo-2",
"name": "OpenSEO",
"url": "https://www.producthunt.com/posts/openseo-2",
"alias": "openseo-2",
"launch_id": "1272262",
"tagline": "The open source Semrush alternative",
"votes_count": 354,
"comments_count": 39,
"daily_rank": 2,
"weekly_rank": 9,
"monthly_rank": 12,
"topics": [],
"image": "https://ph-files.imgix.net/2c78fe4a-262c-48b2-a376-365b77bf6eeb.png?auto=format&fit=crop&w=128&h=128",
"product_slug": "openseo",
"product_url": "https://www.producthunt.com/products/openseo",
"featured_at": "2026-10-08T00:01:00-07:00",
"created_at": "2026-10-08T00:01:00-07:00"
},
{
"id": "openswarm-3",
"name": "OpenSwarm",
"url": "https://www.producthunt.com/posts/openswarm-3",
"alias": "openswarm-3",
"launch_id": "1271048",
"tagline": "A swarm of agents, in the same place you work",
"votes_count": 376,
"comments_count": 60,
"daily_rank": 1,
"weekly_rank": 6,
"monthly_rank": 9,
"topics": [],
"image": "https://ph-files.imgix.net/ea2bfd22-7652-444c-b680-8028ef82bdc8.png?auto=format&fit=crop&w=128&h=128",
"product_slug": "openswarm-3",
"product_url": "https://www.producthunt.com/products/openswarm-3",
"featured_at": "2026-10-08T00:01:00-07:00",
"created_at": "2026-10-08T00:01:00-07:00"
}
],
"total_found": null,
"page_count": 1,
"blocked": false,
"proxy_traffic_bytes": 17845
},
"total_points": 2
}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-upvotes \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"user":"kevin","max_items":2}'What teams use it for
Where this field shows up in an actual workflow.
See which kinds of products an active account backs.
Find recent launches that people in your market upvote.
Re-run on a schedule to catch what an account upvotes next.
Compare upvoted launches across several accounts to find overlap.
Coverage, freshness and limits
What this source covers, how fresh it is, and where it stops.
Product Hunt records with a public page.
Read at request time, so the answer reflects the platform as it stands when you ask.
This source returns information Product Hunt shows publicly. Every response carries the session id you can trace.
- —Upvotes are personal activity. Use them as a signal about products, not to profile the individual.
- —Only the latest 200 upvotes per user are available from the platform.
- —The sample returned no total (total_found is null).
Questions, answered
The platform serves only the latest 200 upvotes of a user, so older upvotes cannot be returned.
Related sources
Profile of one Product Hunt user with follower and launch counts.
Launches a user submitted, with votes and ranks.
Comments a user has posted.
Startup directories, funding databases, launch platforms and investor data.
Try product hunt user upvotes on your own data
One request format across every source in the catalog.