Product Hunt User Comments API and MCP — Comment Text, Link and Date
Send a username or profile link and get that user's comments from their activity feed: the comment text, a link to the comment and the date and time it was posted. All pages are read, up to the max_items you set (up to 250).
- You send
- a Product Hunt username or profile link, and how many results to return
- You get back
- the user's comments from their activity feed, with text, link and date
- 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 | Comment id. |
machine.items[].name | string | Label for the comment, in the form Comment <id>. |
machine.items[].url | string | Link to the comment on the page it was posted under. |
machine.items[].comment_id | string | Numeric comment id. |
machine.items[].body | string | Comment text. |
machine.items[].created_at | string | Date and time the comment was posted. |
Example response
A real response, as returned.
{
"session_id": "11111111-1111-1111-1111-111111111111",
"kind": "producthunt_users_comments",
"user": "kevin",
"max_items": 2,
"start_page": 1,
"partial": false,
"human": "# Product Hunt — user comments\n\n- **User:** kevin\n- **Results:** 2\n- **Proxy traffic:** 34.6 KB",
"machine": {
"total_items": 2,
"first_item": {
"id": "5887202",
"name": "Comment 5887202",
"url": "https://www.producthunt.com/products/clueso?comment=5887202",
"comment_id": "5887202",
"body": "Congrats on the launch, @neel_balar 🚀. Connecting video generation directly to agents like Claude and Cursor via MCP is a great move. Being able to feed it a reference video or deck and get back an ed",
"created_at": "2026-09-22T01:10:12-07:00"
},
"items": [
{
"id": "5887202",
"name": "Comment 5887202",
"url": "https://www.producthunt.com/products/clueso?comment=5887202",
"comment_id": "5887202",
"body": "Congrats on the launch, @neel_balar 🚀. Connecting video generation directly to agents like Claude and Cursor via MCP is a great move. Being able to feed it a reference video or deck and get back an ed",
"created_at": "2026-09-22T01:10:12-07:00"
},
{
"id": "5655884",
"name": "Comment 5655884",
"url": "https://www.producthunt.com/products/promptql?comment=5655884",
"comment_id": "5655884",
"body": "Excited to launch this today. Congrats @tanmaig and @rajoshi_ghosh on the launch! 🚀 Love the concept of a AI-native workspace built around captured team context rather than just isolated chats. As tea",
"created_at": "2026-07-23T07:41:14-07:00"
}
],
"total_found": null,
"page_count": 1,
"blocked": false,
"proxy_traffic_bytes": 35394
},
"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-comments \
-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 how active a maker or investor is in product discussions before you approach them.
Find which products a user comments on, from the links.
Re-run on a schedule to follow what a given account says on launches.
Read comments from a known industry voice as input to product research.
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.
- —Comments are personal posts. Use them as context for product research, not to profile the person.
- —The comment text may be shortened in the response; open the link to read a long comment in full.
- —Only comments in the activity feed are returned; the sample returned no total (total_found is null).
Questions, answered
The ones shown in the user's activity feed under the comments filter.
Related sources
Profile of one Product Hunt user with follower and launch counts.
Launches a user submitted, with votes and ranks.
Launches a user upvoted, newest first.
Startup directories, funding databases, launch platforms and investor data.
Try product hunt user comments on your own data
One request format across every source in the catalog.