Product Hunt Launches Feed MCP Server
Provides tools for retrieving Product Hunt launch feed data, including launch names, maker names, product websites, company domains, X and LinkedIn links, votes, rank, and topics, with filtering by dates, topics, keywords, and minimum votes.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Product Hunt Launches Feed MCP ServerGet yesterday's AI launches with makers and domains"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Product Hunt Launches Feed MCP Server
An MCP server for the Mamba Labs Product Hunt Launches Feed actor on Apify. Pick the days, and get one row per Product Hunt launch with the maker names, the product's website and company domain, its X and LinkedIn links, votes, rank, and topics.
What's Inside
Related MCP server: mcp-producthunt
What it does
The actor reads Product Hunt's public daily launch pages and each launch's product page through the Apify proxy, with robots.txt obeyed. The public daily page shows the day's top featured launches. With your own Product Hunt developer token (product_hunt_token), the daily lists come from the official Product Hunt API instead, and include_unfeatured adds the launches Product Hunt did not feature. Filter by topic, keyword, or minimum votes, and use only_new on a schedule. Each day also returns one free summary row.
All of the work runs on Apify. This package is a thin client that starts the actor run, waits for it, and hands back the dataset rows.
Quick start
You need Node.js 18 or newer and an Apify account with an API token.
Add this to your Claude Desktop config (claude_desktop_config.json), Cursor, or any MCP client:
{
"mcpServers": {
"mamba-product-hunt-launches-feed": {
"command": "npx",
"args": ["-y", "@mambalabsdev/mcp-product-hunt-launches-feed"],
"env": {
"APIFY_TOKEN": "your-apify-token"
}
}
}
}Restart the client. The get_product_hunt_launches tool appears.
Prerequisites
Node.js 18 or newer.
An Apify API token from console.apify.com/account/integrations, set as
APIFY_TOKEN. The server lists its tool without a token; a call needs one.
Example prompts
"List yesterday's Product Hunt launches in AI with their company domains and makers."
"Which developer tools launched on Product Hunt this week with more than 200 votes?"
"Get the launches of 2026-10-27 into a table."
Tool
get_product_hunt_launches. One tool. Example arguments:
{
"days_back": 1,
"topics": [
"Artificial Intelligence"
],
"max_launches": 50
}Inputs
Every buyer facing input of the actor. Omitted inputs take the actor's own defaults.
Input | Type | Required | Description |
| integer | no | The last N full days, Pacific time. Default 1. |
| array | no | Specific days as YYYY-MM-DD, up to 31. |
| boolean | no | Also read today's list. Default false. |
| array | no | Product Hunt topics by name or slug. |
| array | no | Words to find in the name, tagline, or topics. |
| integer | no | Minimum votes. Default 0. |
| integer | no | Launch rows per run. Default 100. |
| boolean | no | Read product pages for website, domain, makers, socials. Default true. |
| boolean | no | Skip launches an earlier run returned. Default false. |
| string | no | Name for the only new launches memory. |
| string | no | Your own Product Hunt developer token, optional. |
| boolean | no | With your token, add unfeatured launches. Default false. |
| string | no | Optional cost cap for the run. |
Pricing
Pay per event on Apify, billed to your Apify account. Prices in USD.
Event | Free plan | Bronze | Silver | Gold |
| $0.00425 | $0.004038 | $0.003825 | $0.003613 |
| $0.002 | $0.002 | $0.002 | $0.002 |
Day summary rows, input refusal rows, launches whose product page could not be read, and launches skipped with only_new are free. Mamba Labs pays the platform costs of the run, Apify proxy traffic included.
Full actor documentation
apify.com/mambalabs/product-hunt-launches-feed
License
MIT. See LICENSE.
Available Tools
1 toolget_product_hunt_launchesGet Product Hunt launchesARead-onlyIdempotent
Get the Product Hunt launches of the days you pick, one flat row per launch: name, tagline, daily rank, votes, comments, topics, maker names with their headlines, maker profile links, the product's website and company domain, and its X and LinkedIn links, plus one free summary row per day. Filter by topic, keyword, or minimum votes; only_new returns only launches an earlier run did not. Public pages are read through the Apify proxy with robots.txt obeyed; an optional Product Hunt developer token of your own reads the daily lists from the official API and adds unfeatured launches. A run that does not succeed is returned as an error with its run ID. Read-only; requires an APIFY_TOKEN and is billed per launch row.
| Name | Required | Description | Default |
|---|---|---|---|
| dates | No | Specific launch days as YYYY-MM-DD, up to 31. | |
| topics | No | Product Hunt topics by name or slug, for example Artificial Intelligence, developer-tools. | |
| keywords | No | Words to find in the launch name, tagline, or topics. | |
| only_new | No | Skip launches an earlier run with the same state_key returned (free). Default false. | |
| days_back | No | The last N full days, in Product Hunt's day (Pacific time). 1 is yesterday. Default 1. Ignored when dates is set. | |
| min_votes | No | Keep launches with at least this many votes. Default 0. | |
| state_key | No | Optional name for the only new launches memory. | |
| max_launches | No | Launch rows per run. Default 100. | |
| include_today | No | Also read today's list, which is still filling. Default false. | |
| max_charge_usd | No | Optional. The run stops before a charge that would pass this amount. | |
| include_unfeatured | No | Needs product_hunt_token. Also return unfeatured launches. Default false. | |
| open_product_pages | No | Read each product page for website, domain, makers, and socials. Default true. | |
| product_hunt_token | No | Optional. Your own Product Hunt developer token, for the official API route. Never stored or logged. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnly, openWorld, idempotent, non-destructive), the description discloses the access path (Apify proxy, robots.txt obeyed), auth requirement (APIFY_TOKEN), per-launch-row billing, the max_charge_usd stop guard, that the token is never stored or logged, and that failed runs surface as errors with a run ID. That is substantial context an agent cannot get from the annotations alone.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
It is a dense paragraph but front-loaded with the core purpose and output shape before filters and operational caveats. Nearly every clause carries information, though the run-on sentence structure and stacking of billing/auth notes makes it slightly harder to scan than it needs to be.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 13 all-optional parameters and no output schema, the description compensates by describing the returned row fields, the free summary row, the two access routes, and failure behavior. An agent has enough to decide whether to call it and to predict the response without a schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3, but the description adds real meaning: only_new's memory semantics (free), include_unfeatured's dependency on product_hunt_token, and the effect of open_product_pages on which fields appear. It goes beyond restating the schema without fully explaining every parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource ('Get the Product Hunt launches of the days you pick') and then enumerates the exact row shape returned, including daily rank, votes, makers, and socials. There are no siblings to disambiguate, and the flat-row-per-launch output model plus free summary row is stated explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It names the selection mechanisms (dates, days_back, topics, keywords, min_votes) and explains the conditional modes: only_new returns launches an earlier run did not, and the optional developer token adds unfeatured launches. What's missing is any explicit statement of when not to use it or trade-offs between the date-selection paths, so it stops short of full 5-level guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v1.0.0- First observed
get_product_hunt_launches
TDQS
Scored across 1 tool
There is only one tool, so there is no possibility of misselection between overlapping tools. Its purpose (fetch Product Hunt launch rows for chosen days with filters) is stated unambiguously in the description.
The single name get_product_hunt_launches follows a clear verb_noun snake_case convention. With one tool there is no risk of mixed conventions, and the name is self-describing.
The domain is a single read-only feed operation, and the one tool absorbs filtering, topic/keyword/vote thresholds, and incremental 'only_new' behavior, so it genuinely earns its place rather than being a trivial wrapper. It is still a one-tool surface, which feels thin if consumers later want per-product detail or comment retrieval.
For a feed reader the surface is largely complete: daily rows, maker metadata, links, topic/keyword/vote filters, incremental runs, and error reporting with run IDs. Minor gaps remain around deeper per-launch detail (e.g., comment bodies or multi-day historical backfill beyond the picked days), but core read workflows are covered.
Maintenance
Related MCP Connectors
Product Hunt launches, votes, makers, comments via the official API. Pay per result.
Search new software launches, read product pages, find alternatives and see daily upvote rankings.
Search new product launches from indie makers and read their details. Read-only, no auth.
Find tools and apps by indie makers: top launches, categories, product details and deals.
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