# Product Hunt Scraper — Launches, Upvotes & Maker Data \[Daily] (`knotless_cadence/product-hunt-scraper`) Actor Scrape Product Hunt launches — product names, descriptions, votes, makers, comments. Track new products, analyze trends, and discover competitors. Export structured data. Custom pipeline: $100 pilot, spinov001@gmail.com - **URL**: https://apify.com/knotless\_cadence/product-hunt-scraper.md - **Developed by:** [Alex](https://apify.com/knotless_cadence) (community) - **Categories:** Social media, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN 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/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use 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 ## Product Hunt Scraper Scrape Product Hunt launches, votes, and product data — track daily leaderboards, discover trending products by category, and monitor the startup ecosystem. Perfect for market research and competitive analysis. ### Features - **Daily leaderboard scraping** — extract top products from any date's leaderboard - **Category browsing** — scrape products by topic (AI, SaaS, Developer Tools, Marketing, etc.) - **Search functionality** — find products by keyword across all of Product Hunt - **Historical data** — scrape past launches up to 7+ days back - **Rich product data** — name, tagline, votes, comments, website URL, topics, makers, and thumbnails - **Next.js data extraction** — parses embedded JSON data for maximum field coverage - **Auto-pagination** — collects up to 200+ products per run ### Output Example ```json { "name": "AI Code Reviewer", "tagline": "Automated code reviews powered by GPT-5", "url": "https://www.producthunt.com/posts/ai-code-reviewer", "votes": 847, "comments": 123, "website": "https://aicodereview.com", "thumbnail": "https://ph-files.imgix.net/...", "topics": ["Developer Tools", "Artificial Intelligence", "Productivity"], "makers": ["Sarah Chen", "Mike Johnson"], "createdAt": "2026-03-17T08:00:00.000Z", "scrapedAt": "2026-03-18T12:00:00.000Z" } ```` ### Use Cases - **Market research** — discover new products and startups launching in your industry every day - **Competitive monitoring** — track competitor launches, vote counts, and community reception - **Trend analysis** — identify trending product categories and emerging technology patterns - **Investor research** — screen early-stage startups by traction (votes, comments) and category - **Inspiration database** — build a dataset of product ideas, taglines, and positioning strategies ### Input Parameters | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `scrapeDaily` | Boolean | `true` | Whether to scrape daily leaderboards | | `daysToScrape` | Number | `7` | Number of days back to scrape (1-30) | | `categories` | Array | `[]` | Product Hunt topics to scrape (e.g., `["artificial-intelligence", "saas"]`) | | `searchQueries` | Array | `[]` | Keywords to search for products | | `maxProducts` | Number | `200` | Maximum total products to extract | ### Cost Estimation - \~$0.50 per 200 products extracted - A full week of daily leaderboards takes under 5 minutes - Free tier: up to 50 products with Apify free plan ### FAQ **Q: Can I get all products from a specific launch date?** A: Yes. Set `scrapeDaily: true` and `daysToScrape: 1` to get today's launches, or increase the number to scrape multiple days of leaderboards. **Q: Does it extract the actual product website URL?** A: Yes. When available, the scraper extracts the external website URL (not just the Product Hunt page), so you can visit the actual product. **Q: How often is Product Hunt data updated?** A: Product Hunt posts new products daily starting at 12:01 AM PST. Vote and comment counts are live at the time of scraping. # Actor input Schema ## `scrapeDaily` (type: `boolean`): Whether to scrape products from Product Hunt daily leaderboards ## `daysToScrape` (type: `integer`): Number of past days to scrape from the leaderboard ## `categories` (type: `array`): Product Hunt topics to scrape (e.g., 'artificial-intelligence', 'developer-tools', 'marketing') ## `searchQueries` (type: `array`): Search Product Hunt for specific terms ## `maxProducts` (type: `integer`): Maximum total number of products to extract across all sources ## Actor input object example ```json { "scrapeDaily": true, "daysToScrape": 7, "categories": [], "searchQueries": [], "maxProducts": 200 } ``` # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("knotless_cadence/product-hunt-scraper").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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("knotless_cadence/product-hunt-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).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 knotless_cadence/product-hunt-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=knotless_cadence/product-hunt-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Product Hunt Scraper — Launches, Upvotes & Maker Data [Daily]", "description": "Scrape Product Hunt launches — product names, descriptions, votes, makers, comments. Track new products, analyze trends, and discover competitors. Export structured data. Custom pipeline: $100 pilot, spinov001@gmail.com", "version": "1.0", "x-build-id": "oaqXFPsaBFfcSW05a" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/knotless_cadence~product-hunt-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-knotless_cadence-product-hunt-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/knotless_cadence~product-hunt-scraper/runs": { "post": { "operationId": "runs-sync-knotless_cadence-product-hunt-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/knotless_cadence~product-hunt-scraper/run-sync": { "post": { "operationId": "run-sync-knotless_cadence-product-hunt-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "scrapeDaily": { "title": "Scrape Daily Leaderboards", "type": "boolean", "description": "Whether to scrape products from Product Hunt daily leaderboards", "default": true }, "daysToScrape": { "title": "Days to Scrape", "minimum": 1, "maximum": 30, "type": "integer", "description": "Number of past days to scrape from the leaderboard", "default": 7 }, "categories": { "title": "Categories/Topics", "type": "array", "description": "Product Hunt topics to scrape (e.g., 'artificial-intelligence', 'developer-tools', 'marketing')", "default": [], "items": { "type": "string" } }, "searchQueries": { "title": "Search Queries", "type": "array", "description": "Search Product Hunt for specific terms", "default": [], "items": { "type": "string" } }, "maxProducts": { "title": "Max Products", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum total number of products to extract across all sources", "default": 200 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```