# Tech Events Aggregator — Luma & Partiful with Auto-Tagging (`avinashchby/tech-events-aggregator`) Actor Scrape tech events from Lu.ma and Partiful. Auto-tags each event as hackathon, demo day, investor dinner, conference, workshop, or networking. Outputs Notion/Airtable-ready JSON with organizer, tags, format, and ticket info. - **URL**: https://apify.com/avinashchby/tech-events-aggregator.md - **Developed by:** [Avinash](https://apify.com/avinashchby) (community) - **Categories:** Automation, 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 ## Tech Events Aggregator — Luma & Partiful Scraper > **What this actor does:** Scrapes tech events from Lu.ma (lu.ma/discover) and Partiful (partiful.com/explore), auto-tags each event (hackathon, demo day, investor dinner, conference, workshop, networking), and exports Notion/Airtable-ready JSON. ### Features - Aggregates events from **Lu.ma** and **Partiful** — the two leading platforms for tech and startup events - **Auto-tagging**: classifies each event as hackathon, demo-day, investor-dinner, conference, workshop, networking, or other - Filter by keyword, city, event tags, and price (free/paid) - Output fields: name, date, location, tags, organizer, ticket price, description, image URL, source - JSON output compatible with Notion databases, Airtable bases, Make.com, and Zapier ### Use Cases - **Startup ecosystem mapping**: Find all hackathons and demo days in your city this month - **Investor outreach**: Discover investor dinners and pitch events to attend or sponsor - **Event curation**: Build tech event newsletters automatically - **Community building**: Track conferences and networking events in your niche (AI, Web3, climate) - **Sales prospecting**: Monitor who's running events in your target market ### Input Parameters | Parameter | Type | Description | Default | |-----------|------|-------------|---------| | `sources` | array | Platforms: `["luma", "partiful"]` | both | | `query` | string | Keyword filter (e.g. "AI", "Web3", "climate tech") | — | | `city` | string | City filter (e.g. "San Francisco", "London") | — | | `tags` | array | Filter by tag: `["hackathon", "demo-day", ...]` | all tags | | `priceType` | string | "free", "paid", or "both" | "both" | | `maxResults` | number | Max events to return | 100 | ### Output Fields | Field | Description | |-------|-------------| | `name` | Event title | | `url` | Event URL (lu.ma or partiful.com) | | `startAt` | ISO 8601 start datetime | | `endDate` | ISO 8601 end datetime | | `description` | Plain text description | | `location` | "City, Country" string | | `venue` | Object: address, city, country, lat, lng | | `isOnline` | Boolean | | `tags` | Array of auto-detected tags | | `isFree` | Boolean | | `ticketPrice` | Price string or "Free" | | `organizer` | Host/organizer name | | `imageUrl` | Event cover image | | `source` | "luma" or "partiful" | | `scrapedAt` | Scrape timestamp | ### Auto-Tagging Logic Events are classified by scanning title and description: | Tag | Trigger keywords | |-----|-----------------| | `hackathon` | "hackathon", "hack day", "build-a-thon" | | `demo-day` | "demo day", "showcase", "pitch day", "demo night" | | `investor-dinner` | "investor", "VC dinner", "funder", "venture capital" | | `conference` | "conference", "summit", "symposium", "congress" | | `workshop` | "workshop", "masterclass", "bootcamp", "hands-on" | | `networking` | "networking", "happy hour", "mixer", "meetup", "social" | | `other` | (default if no pattern matches) | Events can have multiple tags. ### Example Input ```json { "sources": ["luma", "partiful"], "query": "AI startup", "city": "San Francisco", "tags": ["hackathon", "demo-day", "networking"], "priceType": "both", "maxResults": 50 } ```` ### Example Output ```json { "name": "SF AI Founders Hackathon", "url": "https://lu.ma/sf-ai-hackathon-2026", "startAt": "2026-05-10T09:00:00.000Z", "location": "San Francisco, US", "tags": ["hackathon", "networking"], "isFree": true, "ticketPrice": "Free", "organizer": "AI SF Community", "source": "luma", "scrapedAt": "2026-04-23T10:00:00.000Z" } ``` ### Questions answered by this actor - What hackathons are coming up in San Francisco this month? - Where are the AI networking events in New York? - Which demo days and pitch events are happening in London? - What free tech workshops are available in my city? - Who's organizing the most investor dinners in the Bay Area? ### Frequently Asked Questions **Does this require any API keys?** No. Events are scraped from public pages on lu.ma and partiful.com. **How often should I run this?** Luma and Partiful refresh their discover pages frequently. Running daily or every few days keeps your dataset current. **Can I filter to only free events?** Yes — set `priceType: "free"`. **Can I get events from only one source?** Yes — set `sources: ["luma"]` or `sources: ["partiful"]`. # Actor input Schema ## `sources` (type: `array`): Which platforms to scrape: 'luma', 'partiful', or both. Default: \["luma", "partiful"]. ## `query` (type: `string`): Keywords to filter events (e.g. 'AI', 'crypto', 'startup') ## `city` (type: `string`): City to filter by (e.g. 'San Francisco', 'New York') ## `tags` (type: `array`): Only return events matching these auto-tags. Options: hackathon, demo-day, investor-dinner, conference, workshop, networking, other ## `priceType` (type: `string`): Filter by ticket price ## `maxResults` (type: `integer`): Maximum total events to return. Default: 100. ## Actor input object example ```json { "sources": [ "luma", "partiful" ], "priceType": "both", "maxResults": 100 } ``` # 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("avinashchby/tech-events-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("avinashchby/tech-events-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 avinashchby/tech-events-aggregator --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=avinashchby/tech-events-aggregator", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Tech Events Aggregator — Luma & Partiful with Auto-Tagging", "description": "Scrape tech events from Lu.ma and Partiful. Auto-tags each event as hackathon, demo day, investor dinner, conference, workshop, or networking. Outputs Notion/Airtable-ready JSON with organizer, tags, format, and ticket info.", "version": "1.0", "x-build-id": "14JmMqVTTjQwjwXhu" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/avinashchby~tech-events-aggregator/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-avinashchby-tech-events-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/avinashchby~tech-events-aggregator/runs": { "post": { "operationId": "runs-sync-avinashchby-tech-events-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/avinashchby~tech-events-aggregator/run-sync": { "post": { "operationId": "run-sync-avinashchby-tech-events-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", "properties": { "sources": { "title": "Sources to scrape", "type": "array", "description": "Which platforms to scrape: 'luma', 'partiful', or both. Default: [\"luma\", \"partiful\"].", "items": { "type": "string" }, "default": [ "luma", "partiful" ] }, "query": { "title": "Search keyword", "type": "string", "description": "Keywords to filter events (e.g. 'AI', 'crypto', 'startup')" }, "city": { "title": "City", "type": "string", "description": "City to filter by (e.g. 'San Francisco', 'New York')" }, "tags": { "title": "Event tags filter", "type": "array", "description": "Only return events matching these auto-tags. Options: hackathon, demo-day, investor-dinner, conference, workshop, networking, other", "items": { "type": "string" } }, "priceType": { "title": "Price filter", "enum": [ "free", "paid", "both" ], "type": "string", "description": "Filter by ticket price", "default": "both" }, "maxResults": { "title": "Max results", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum total events to return. Default: 100.", "default": 100 } } }, "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 } } } } } } } } } } ```