# Hackathon Aggregator — 6 Platforms in One (`aurumworks/hackathon-aggregator`) Actor Scrape hackathons from Devpost, MLH, DoraHacks, Devfolio, Unstop, and HackerEarth. Get event names, dates, prizes, locations, themes, participant counts, and deadlines. All 6 platforms in one unified dataset. - **URL**: https://apify.com/aurumworks/hackathon-aggregator.md - **Developed by:** [Aryan Saxena](https://apify.com/aurumworks) (community) - **Categories:** Automation, Integrations, Other - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $11.00 / 1,000 results 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 ## Hackathon Aggregator — Scrape Hackathons from 6 Platforms **Find every hackathon in one place.** This actor scrapes upcoming and past hackathons from Devpost, MLH, DoraHacks, Devfolio, Unstop, and HackerEarth — and delivers them in a single, unified dataset. No more checking six different websites. Run it on the Apify platform to get API access, scheduling, and integrations with Google Sheets, Slack, Zapier, and more. ### Why use Hackathon Aggregator? - **6 platforms, 1 dataset** — Devpost, MLH, DoraHacks, Devfolio, Unstop, and HackerEarth combined - **Unified schema** — every hackathon has the same fields regardless of source - **Filter by status** — upcoming, past, or all - **Keyword search** — find hackathons by topic (AI, blockchain, health, etc.) - **No proxy needed** — all sources are public pages - **Schedule it** — run daily or weekly to never miss a hackathon ### Who is this for? - Students looking for hackathons to join - Recruiters scouting talent at hackathon events - Companies planning hackathon sponsorships - Newsletter creators covering the hackathon ecosystem - Developers building hackathon aggregator apps ### How to use Hackathon Aggregator 1. Click **Try for free** on this page 2. Select which platforms you want to scrape (or leave all 6 selected) 3. Choose **upcoming**, **past**, or **all** hackathons 4. Optionally enter a keyword like "AI" or "Web3" 5. Click **Start** and wait for results 6. Download your data as JSON, CSV, or Excel ### Input | Field | Type | Description | Default | |-------|------|-------------|---------| | Sources | array | Platforms to scrape | All 6 | | Status | string | upcoming, past, or all | upcoming | | Max Results | integer | Max hackathons per source (1–500) | 50 | | Search Query | string | Optional keyword filter | — | ### Output Each hackathon record contains: ```json { "source": "devpost", "title": "AI Hackathon 2026", "url": "https://ai-hackathon.devpost.com", "tagline": "Build the future of AI", "dates": "May 1 - May 20, 2026", "prize": "$50,000 in prizes", "participants": "4,734", "location": "Online", "themes": ["Machine Learning/AI", "Beginner Friendly"], "isOnline": true, "daysLeft": "21 days left" } ```` You can download the dataset in various formats such as JSON, HTML, CSV, or Excel. ### Data fields | Field | Description | |-------|-------------| | source | Platform name (devpost, mlh, dorahacks, devfolio, unstop, hackerearth) | | title | Hackathon name | | url | Direct link to the hackathon page | | dates | Event date range | | prize | Prize pool amount | | participants | Number of participants or registrations | | location | Physical location or "Online" / "Virtual" | | themes | Tags and categories | | isOnline | Whether the event is online | | daysLeft | Time remaining until deadline | ### How much does it cost to scrape hackathons? This actor uses minimal compute resources. A typical run scraping all 6 platforms costs less than **$0.05** in platform usage. The Apify free tier includes enough credits to run this actor multiple times per day. ### Tips - Start with 1–2 platforms to test, then expand to all 6 - Use the **Search Query** field to narrow results by topic - Schedule weekly runs to build a historical dataset of hackathons over time - Connect to Google Sheets via Apify integrations for a live hackathon tracker ### Supported platforms | Platform | Focus | Coverage | |----------|-------|----------| | Devpost | General hackathons | Global, 13,000+ hackathons | | MLH | Student hackathons | Global, university-focused | | DoraHacks | Web3 / blockchain | Global, crypto/DeFi focus | | Devfolio | Indian hackathons | India + global | | Unstop | Indian competitions | India, 7M+ users | | HackerEarth | Enterprise hackathons | Global, corporate challenges | ### FAQ **Is it legal to scrape these platforms?** This actor accesses only publicly available hackathon listing pages. No login or authentication is required. Always review each platform's terms of service before use. **How often is the data updated?** The data is live — every run fetches the latest listings. Schedule runs as frequently as you need. **Can I filter by country or region?** Not directly, but you can use the Search Query field with location keywords, or filter the output dataset after scraping. **I found a bug or have a feature request.** Please open an issue in the Issues tab. We actively maintain this actor. # Actor input Schema ## `sources` (type: `array`): Which platforms to scrape hackathons from ## `status` (type: `string`): Filter by hackathon status ## `maxResults` (type: `integer`): Maximum number of hackathons to scrape per source ## `searchQuery` (type: `string`): Optional keyword to filter hackathons (e.g. AI, blockchain, health) ## Actor input object example ```json { "sources": [ "devpost", "mlh", "devfolio", "dorahacks", "unstop", "hackerearth" ], "status": "upcoming", "maxResults": 50 } ``` # 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("aurumworks/hackathon-aggregator").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("aurumworks/hackathon-aggregator").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 aurumworks/hackathon-aggregator --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=aurumworks/hackathon-aggregator", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Hackathon Aggregator — 6 Platforms in One", "description": "Scrape hackathons from Devpost, MLH, DoraHacks, Devfolio, Unstop, and HackerEarth. Get event names, dates, prizes, locations, themes, participant counts, and deadlines. All 6 platforms in one unified dataset.", "version": "0.1", "x-build-id": "XV1CxR1BoQE4Pqk8m" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/aurumworks~hackathon-aggregator/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-aurumworks-hackathon-aggregator", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/aurumworks~hackathon-aggregator/runs": { "post": { "operationId": "runs-sync-aurumworks-hackathon-aggregator", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/aurumworks~hackathon-aggregator/run-sync": { "post": { "operationId": "run-sync-aurumworks-hackathon-aggregator", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "sources" ], "properties": { "sources": { "title": "Sources", "type": "array", "description": "Which platforms to scrape hackathons from", "default": [ "devpost", "mlh", "devfolio", "dorahacks", "unstop", "hackerearth" ], "items": { "type": "string" } }, "status": { "title": "Hackathon Status", "enum": [ "upcoming", "past", "all" ], "type": "string", "description": "Filter by hackathon status", "default": "upcoming" }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of hackathons to scrape per source", "default": 50 }, "searchQuery": { "title": "Search Query", "type": "string", "description": "Optional keyword to filter hackathons (e.g. AI, blockchain, health)" } } }, "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": 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"type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```