# Product Hunt Scraper (`ef12/product-hunt-scraper`) Actor Scrape Product Hunt posts by category and sort order. Get product names, taglines, upvotes, makers, topics, and comment counts via the GraphQL API. - **URL**: https://apify.com/ef12/product-hunt-scraper.md - **Developed by:** [Daniel Wilson](https://apify.com/ef12) (community) - **Categories:** Developer tools - **Stats:** 1 total users, 0 monthly users, 33.3% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## 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 **Product Hunt Scraper** lets you pull fresh product launches, trending tools, and top-voted posts from [Product Hunt](https://www.producthunt.com/) using the official GraphQL API — no browser emulation, no HTML parsing, no CAPTCHAs. You get clean JSON with every field that matters: name, tagline, upvotes, maker, topics, comments, and dates. Built as an [Apify Actor](https://apify.com/actors), it runs on a serverless platform with built-in scheduling, proxy-free API access, data export to JSON/CSV/Excel, and integration with Zapier, Make, and REST webhooks. One API call, structured data back. ### Why use Product Hunt Scraper? - **Market research** — Track which products in your category are gaining traction. See what taglines and positioning resonate. - **Competitor monitoring** — Watch your competitors' launches: when they ship, how many upvotes they get, what topics they target. - **Investor sourcing** — Identify early-stage products with strong community traction. Upvote velocity and comment activity are leading indicators. - **Content inspiration** — Product Hunt is a firehose of startup ideas, feature announcements, and product positioning examples. - **Data pipeline feed** — Pull daily batches into a warehouse for trend analysis, dashboards, or ML models trained on product-market fit signals. - **Tool discovery** — Filter by category like `developer-tools` or `artificial-intelligence` to find new tools worth trying. ### How to use Product Hunt Scraper #### 1. Get a Product Hunt API token 1. Go to [Product Hunt Developer Settings](https://www.producthunt.com/v2/oauth/applications). 2. Create a new OAuth application (it's free). 3. Generate a **Personal Access Token**. 4. Copy the token — you'll need it to authenticate API calls. #### 2. Set the token as a secret Run this locally: ```bash apify secrets add PRODUCTHUNT_TOKEN your_token_here ```` When you push to the Apify Cloud, the secret travels with your Actor automatically. #### 3. Configure your run Open the **Input** tab and set: | Field | Description | Default | | ------- | ------------- | --------- | | Sort Order | How posts are sorted: `newest`, `top`, or `featured` | `newest` | | Category | Topic slug filter (e.g. `developer-tools`) — leave empty for all | — | | Lookback Days | How many days to scan (top sort) | 7 | | Max Results | Total posts to return (max 100) | 25 | | Min Upvotes | Filter out posts below this threshold | 0 | #### 4. Run it ```bash apify run --input-file=test-input.json ``` Or in the Apify Console, click **Run** after filling in the input form. ### Output Each run pushes structured JSON to the Actor's default dataset. You can download the dataset in JSON, HTML, CSV, or Excel. ```json [ { "name": "Example Product", "tagline": "AI-powered tool for developers", "url": "https://www.producthunt.com/posts/example-product", "website_url": "https://example.com", "upvotes": 342, "maker": "Jane Developer", "topics": ["Developer Tools", "AI"], "created_at": "2025-06-15T12:00:00Z", "comment_count": 28 } ] ``` #### Data table | Field | Type | Description | | ------- | ------ | ------------- | | `name` | string | Product name | | `tagline` | string | One-line description | | `url` | string | Product Hunt post URL | | `website_url` | string | Product's own website | | `upvotes` | integer | Total upvotes | | `maker` | string | Creator / submitter name | | `topics` | array of strings | Tags / categories | | `created_at` | string (ISO 8601) | Post date | | `comment_count` | integer | Number of comments | ### How much does it cost to scrape Product Hunt? This Actor uses pay-per-event (PPE) billing: | Event | Price | |-------|-------| | `apify-actor-start` | $0.00005 | | `result` (per result, after 10 free) | $0.003 | The first **10 results per run are free**. After that, each result costs $0.003. A run of 50 results costs about $0.00005 + (40 × $0.003) = **$0.12**. A run of 100 results costs about $0.00005 + (90 × $0.003) = **$0.27**. There are no hidden infrastructure costs — the Apify free tier includes 10 free platform usage hours per month. ### Tips & advanced options - **Category slugs**: Common topics include `artificial-intelligence`, `developer-tools`, `design`, `productivity`, `marketing`, `saas`, `open-source`, `api`, `data-analytics`, `security`, `mobile`, `chrome-extensions`. Browse [Product Hunt topics](https://www.producthunt.com/topics) to find the exact slug. - **Limiting compute units**: Set `max_results` as low as your use case allows. Filtering with `min_upvotes` also reduces wasted results. - **Scheduling**: In the Apify Console, set a daily or weekly schedule to keep a rolling dataset of recent launches. - **No proxy needed**: This Actor calls the official API — no IP rotation or residential proxies required. - **Accuracy**: API returns un-filtered data. Post-scrape filtering with `min_upvotes` happens on results the API already returned, so requesting slightly more than your target can help if your upvote threshold is high. ### FAQ, disclaimers, and support **Is scraping Product Hunt legal?**\ This Actor uses Product Hunt's official GraphQL API with proper authentication. You are accessing the same data the API is designed to serve. Always review Product Hunt's [Terms of Service](https://www.producthunt.com/terms) before use. **What if my token doesn't work?**\ Make sure the token is set as the `PRODUCTHUNT_TOKEN` environment variable / Apify secret. The Actor expects the token in the `Authorization: Bearer ` header. **Known limitations** - The Product Hunt API may rate-limit high-frequency requests. The Actor respects this by fetching in moderate page sizes. - Topic slug availability depends on Product Hunt's taxonomy — unknown slugs return empty results rather than an error. **Need help?**\ Open an issue in this repository for bug reports or feature requests. For custom scraping solutions or enterprise needs, reach out via the Apify platform. ### Technical details This Actor calls `https://api.producthunt.com/v2/api/graphql` with an `Authorization: Bearer` header. It uses `httpx` for async HTTP and the Apify Python SDK for dataset storage and PPE metering. No browser, no crawling — just GraphQL queries and structured JSON output. # Actor input Schema ## `sort_order` (type: `string`): How to sort the posts ## `category` (type: `string`): Filter by topic slug, e.g. artificial-intelligence, developer-tools, design, productivity. Leave empty for all. ## `days` (type: `integer`): How many days back to fetch (only applies to 'top' sort) ## `max_results` (type: `integer`): Maximum number of posts to return ## `min_upvotes` (type: `integer`): Only return posts with at least this many upvotes (0 = no filter) ## Actor input object example ```json { "sort_order": "newest", "category": "", "days": 7, "max_results": 25, "min_upvotes": 0 } ``` # Actor output Schema ## `results` (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 '' 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("ef12/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("ef12/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 ef12/product-hunt-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ef12/product-hunt-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Product Hunt Scraper", "description": "Scrape Product Hunt posts by category and sort order. Get product names, taglines, upvotes, makers, topics, and comment counts via the GraphQL API.", "version": "0.0", "x-build-id": "6oafSCPo6diFAbbvf" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ef12~product-hunt-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ef12-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ef12~product-hunt-scraper/runs": { "post": { "operationId": "runs-sync-ef12-product-hunt-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ef12~product-hunt-scraper/run-sync": { "post": { "operationId": "run-sync-ef12-product-hunt-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "sort_order": { "title": "Sort Order", "enum": [ "newest", "top", "featured" ], "type": "string", "description": "How to sort the posts", "default": "newest" }, "category": { "title": "Category (Topic Slug)", "type": "string", "description": "Filter by topic slug, e.g. artificial-intelligence, developer-tools, design, productivity. Leave empty for all.", "default": "" }, "days": { "title": "Lookback Days", "minimum": 1, "maximum": 30, "type": "integer", "description": "How many days back to fetch (only applies to 'top' sort)", "default": 7 }, "max_results": { "title": "Max Results", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of posts to return", "default": 25 }, "min_upvotes": { "title": "Minimum Upvotes", "minimum": 0, "type": "integer", "description": "Only return posts with at least this many upvotes (0 = no filter)", "default": 0 } } }, "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 } } } } } } } } } } ```