# Free Meetup Events Scraper (`alirezaeidgah/meetup-events-scraper`) Actor Scrape Meetup events by location and keyword into a clean structured dataset for research, lead generation, and event tracking. - **URL**: https://apify.com/alirezaeidgah/meetup-events-scraper.md - **Developed by:** [Alireza Eidgah](https://apify.com/alirezaeidgah) (community) - **Categories:** Lead generation, Automation, Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: 5.00 out of 5 stars ## 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 ## Meetup Events Scraper Apify Actor that scrapes Meetup event search results from the Meetup gql2 API and pushes normalized events into the default dataset. ### Input - `url`: Meetup search URL - `max_events`: maximum number of events to collect - `headless`: run browser headless or headed ### Output Each event is pushed as one dataset item with fields: - `city` - `name` - `description` - `cover_image` - `start_at` - `end_at` - `timezone` - `location` - `latitude` - `longitude` - `price` - `currency` - `is_free` - `organizer` - `url` - `category` ### Local run Install dependencies, then run the Actor from the `meetup-actor` directory: ```bash python -m pip install -r requirements.txt python -m playwright install --with-deps python -m src ```` # Actor input Schema ## `country` (type: `string`): Country code or name. ## `state` (type: `string`): State, region, or province. Leave blank if not needed. ## `city` (type: `string`): City to search in. ## `searchKeyword` (type: `string`): Keyword to search for in Meetup event results. ## `maxResults` (type: `integer`): Maximum number of events to return. ## `startDate` (type: `string`): Only return events starting on or after this date. ## `url` (type: `string`): Optional custom Meetup search URL. If set, this overrides the generated location search. ## `headless` (type: `boolean`): Run the browser in headless mode. ## Actor input object example ```json { "country": "us", "state": "", "city": "san francisco", "searchKeyword": "", "maxResults": 20, "startDate": "", "url": "", "headless": true } ``` # Actor output Schema ## `results` (type: `string`): Normalized Meetup events stored in the default dataset. ## `summary` (type: `string`): Run summary stored in the default key-value store. # 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 = { "country": "us", "state": "", "city": "san francisco", "searchKeyword": "", "startDate": "", "url": "" }; // Run the Actor and wait for it to finish const run = await client.actor("alirezaeidgah/meetup-events-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 = { "country": "us", "state": "", "city": "san francisco", "searchKeyword": "", "startDate": "", "url": "", } # Run the Actor and wait for it to finish run = client.actor("alirezaeidgah/meetup-events-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 '{ "country": "us", "state": "", "city": "san francisco", "searchKeyword": "", "startDate": "", "url": "" }' | apify call alirezaeidgah/meetup-events-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=alirezaeidgah/meetup-events-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Free Meetup Events Scraper", "description": "Scrape Meetup events by location and keyword into a clean structured dataset for research, lead generation, and event tracking.", "version": "0.1", "x-build-id": "k5VM0RQ5QAbVUaK75" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/alirezaeidgah~meetup-events-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-alirezaeidgah-meetup-events-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/alirezaeidgah~meetup-events-scraper/runs": { "post": { "operationId": "runs-sync-alirezaeidgah-meetup-events-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/alirezaeidgah~meetup-events-scraper/run-sync": { "post": { "operationId": "run-sync-alirezaeidgah-meetup-events-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", "required": [ "country", "city", "maxResults" ], "properties": { "country": { "title": "Country", "type": "string", "description": "Country code or name.", "default": "us" }, "state": { "title": "State", "type": "string", "description": "State, region, or province. Leave blank if not needed.", "default": "" }, "city": { "title": "City", "type": "string", "description": "City to search in.", "default": "san francisco" }, "searchKeyword": { "title": "Search Keyword", "type": "string", "description": "Keyword to search for in Meetup event results.", "default": "" }, "maxResults": { "title": "Maximum Results", "minimum": 1, "type": "integer", "description": "Maximum number of events to return.", "default": 20 }, "startDate": { "title": "Start Date Range", "type": "string", "description": "Only return events starting on or after this date.", "default": "" }, "url": { "title": "Custom Meetup URL", "type": "string", "description": "Optional custom Meetup search URL. If set, this overrides the generated location search.", "default": "" }, "headless": { "title": "Headless browser", "type": "boolean", "description": "Run the browser in headless mode.", "default": true } } }, "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 } } } } } } } } } } ```