# AI Product Launch Monitor (`toronto_777/ai-product-launch-monitor`) Actor

Monitor public AI product launches from Product Hunt and Hacker News with normalized launch records, keyword matches, and evidence URLs.

- **URL**: https://apify.com/toronto\_777/ai-product-launch-monitor.md
- **Developed by:** [Steven Feng](https://apify.com/toronto_777) (community)
- **Categories:** Lead generation, News, Developer tools
- **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-usage

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## AI Product Launch Monitor

AI Product Launch Monitor tracks new AI-related product launches from public launch feeds and discussions. The MVP reads Product Hunt's public Atom feed and Hacker News launch-style story search results, then returns normalized launch records with source links, taglines, AI keyword matches, and launch scores.

### What It Does

- Reads Product Hunt's public Atom feed without requiring a token.
- Searches Hacker News for recent AI-related Show HN and Launch HN stories.
- Filters launches with configurable AI/product keywords.
- Outputs normalized launch records for market research, sales prospecting, competitive monitoring, and idea discovery.

### Limits

The Product Hunt public feed exposes fewer engagement metrics than the authenticated GraphQL API. This Actor favors low-maintenance public data and can be extended later with an optional Product Hunt API token for votes, comments, maker profiles, and richer categories.

# Actor input Schema

## `sources` (type: `array`):

Sources to scan. Supported values: product\_hunt, hacker\_news.

## `keywords` (type: `array`):

Keywords used to classify AI-related launches.

## `hnLookbackDays` (type: `integer`):

How far back to search Hacker News stories.

## `maxResults` (type: `integer`):

Maximum number of normalized launch records returned.

## Actor input object example

```json
{
  "sources": [
    "product_hunt"
  ],
  "keywords": [
    "AI",
    "agent",
    "LLM",
    "GPT",
    "Claude",
    "copilot",
    "automation",
    "voice",
    "model"
  ],
  "hnLookbackDays": 14,
  "maxResults": 50
}
```

# Actor output Schema

## `results` (type: `string`):

No description

## `summary` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("toronto_777/ai-product-launch-monitor").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("toronto_777/ai-product-launch-monitor").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call toronto_777/ai-product-launch-monitor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,toronto_777/ai-product-launch-monitor"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/fwipjT4AZkJOPWcNd/builds/nFFCulijnBqHysjNq/openapi.json