# Linkedin Events Scraper (`silentflow/linkedin-events-scraper`) Actor Scrape LinkedIn events with full authenticated access. Search by keywords or fetch specific event URLs. Extract titles, descriptions, dates, locations, organizers, attendee counts, speakers, and more. Ideal for sales prospecting, recruiting, market research, and competitive event analysis. - **URL**: https://apify.com/silentflow/linkedin-events-scraper.md - **Developed by:** [SilentFlow](https://apify.com/silentflow) (community) - **Categories:** Social media, Lead generation, Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $19.99/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors ## 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 ## LinkedIn Event Scraper Scrape LinkedIn events with full authenticated access. Search events by keywords or scrape specific event URLs to get complete details including organizer info, attendees, speakers, location, and more. ### ✨ Why use this scraper? - 🔐 **Authenticated access**: Uses your LinkedIn session for rich, complete event data unavailable through public access - 🔍 **Flexible search**: Find events by keywords or scrape specific event URLs directly - 📋 **Complete event details**: Get organizer info, attendees count, speakers, venue address, hashtags, and more - 🌍 **Online and in-person events**: Covers all LinkedIn event types with location and venue details - ⚡ **Fast and reliable**: Scrape 5 events with full details in about 5-10 seconds ### 🎯 Use cases | Industry | Application | |----------|-------------| | **Sales & Business Development** | Find industry events to network with potential clients and partners | | **Recruiting** | Discover hiring events, job fairs, and professional meetups in your field | | **Marketing** | Track competitor events and identify sponsorship or speaking opportunities | | **Market Research** | Monitor event trends, popular topics, and industry gatherings over time | | **Event Planning** | Analyze competing events for timing, format, and audience size insights | | **Lead Generation** | Build lists of events in your niche to identify engaged professional audiences | ### 📥 Input parameters #### Authentication (required) | Parameter | Type | Description | |-----------|------|-------------| | `cookies` | Array | Your LinkedIn cookies exported from browser. Must include `li_at` and `JSESSIONID`. Use a browser extension like EditThisCookie to export them as JSON. | #### Search | Parameter | Type | Description | |-----------|------|-------------| | `keywords` | Array | Keywords to search for LinkedIn events (e.g., "AI conference", "tech meetup"). Each keyword triggers a separate search. | | `eventUrls` | Array | Direct LinkedIn event URLs to scrape (e.g., `https://www.linkedin.com/events/event-name-123456789`). | #### Limits | Parameter | Type | Description | |-----------|------|-------------| | `limit` | Integer | Maximum total number of events to return (default: 50, max: 500). | #### Advanced | Parameter | Type | Description | |-----------|------|-------------| | `userAgent` | String | Custom User-Agent string. Leave empty for automatic rotation. | | `proxy` | Object | Proxy configuration. Residential proxies recommended. | ### 📊 Output data #### Event example ```json { "eventId": "7443970664316882944", "title": "Cocktail de lancement du Partenariat AI Cargo Foundation & UIRR", "description": "AI Cargo Foundation et l'UIRR ont le plaisir de vous inviter au lancement officiel de leur partenariat...", "url": "https://www.linkedin.com/events/7443970664316882944/", "startDateISO": "2026-03-31T15:00:00Z", "endDateISO": "2026-03-31T16:00:00Z", "timezone": "Europe/Brussels", "eventType": "in-person", "location": "Parc des Expositions, 82 Avenue des Nations, Villepinte, Ile-de-France, 93420", "venueAddress": "Parc des Expositions, 82 Avenue des Nations, Villepinte, Ile-de-France, 93420", "city": "Villepinte", "country": "FR", "organizerName": "AI Cargo Foundation", "organizerType": "Company", "organizerProfileUrl": "https://www.linkedin.com/company/aicargo-foundation/", "organizerProfileId": "aicargo-foundation", "numAttendees": 38, "lifecycleState": "FUTURE", "isPrivate": false, "isPremium": false, "scrapedAt": "2026-03-31T13:28:48Z" } ```` ### 🗂️ Data fields | Category | Fields | |----------|--------| | **Basic info** | `eventId`, `title`, `description`, `url`, `coverImage` | | **Timing** | `startDateISO`, `endDateISO`, `timezone` | | **Location** | `eventType`, `location`, `venueAddress`, `city`, `country`, `onlineEventUrl` | | **Organizer** | `organizerName`, `organizerType`, `organizerHeadline`, `organizerProfileUrl`, `organizerProfileId`, `organizerImage` | | **Attendance** | `numAttendees`, `speakers`, `externalUrl` | | **State** | `lifecycleState`, `isPrivate`, `isPremium` | | **Tags** | `hashtags` | | **Metadata** | `scrapedAt` | ### 🚀 Examples #### Search for AI events ```json { "cookies": [ {"name": "li_at", "value": "YOUR_LI_AT_COOKIE"}, {"name": "JSESSIONID", "value": "YOUR_JSESSIONID"} ], "keywords": ["AI conference"], "limit": 20 } ``` #### Scrape specific event URLs ```json { "cookies": [ {"name": "li_at", "value": "YOUR_LI_AT_COOKIE"}, {"name": "JSESSIONID", "value": "YOUR_JSESSIONID"} ], "eventUrls": [ "https://www.linkedin.com/events/ai-summit-2026-7312456789012345678", "https://www.linkedin.com/events/tech-meetup-sf-7298765432109876543" ] } ``` #### Search multiple keywords with limit ```json { "cookies": [ {"name": "li_at", "value": "YOUR_LI_AT_COOKIE"}, {"name": "JSESSIONID", "value": "YOUR_JSESSIONID"} ], "keywords": ["tech meetup", "startup networking", "product management"], "limit": 100 } ``` ### 💻 Integrations #### Python ```python from apify_client import ApifyClient client = ApifyClient("YOUR_APIFY_TOKEN") run_input = { "cookies": [ {"name": "li_at", "value": "YOUR_LI_AT_COOKIE"}, {"name": "JSESSIONID", "value": "YOUR_JSESSIONID"}, ], "keywords": ["AI conference"], "limit": 50, } run = client.actor("YOUR_USERNAME/linkedin-events-scraper").call(run_input=run_input) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(f"{item['title']} - {item['startDateISO']} - {item['numAttendees']} attendees") ``` #### JavaScript ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' }); const input = { cookies: [ { name: 'li_at', value: 'YOUR_LI_AT_COOKIE' }, { name: 'JSESSIONID', value: 'YOUR_JSESSIONID' }, ], keywords: ['AI conference'], limit: 50, }; const run = await client.actor('YOUR_USERNAME/linkedin-events-scraper').call(input); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach(item => { console.log(`${item.title} - ${item.startDateISO} - ${item.numAttendees} attendees`); }); ``` ### 📈 Performance & limits | Metric | Value | |--------|-------| | Speed | ~5-10 seconds for 5 events with full details | | Search results per keyword | Up to 100 events (10 per page, paginated) | | Maximum events per run | 500 | | Default memory | 256 MB | | Recommended proxy | Residential | ### 💡 Tips for best results 1. **Keep your cookies fresh**: LinkedIn cookies expire periodically. If you get authentication errors, re-export your cookies from your browser. 2. **Use direct URLs when possible**: Scraping specific event URLs is the fastest and most reliable method. 3. **Start with a small limit**: Test with 10-20 events first to verify your cookies work, then increase. 4. **Use residential proxies on Apify**: Residential proxies provide the best reliability for LinkedIn scraping. 5. **Combine keywords and URLs**: You can search by keywords and scrape specific URLs in the same run. ### ❓ FAQ **Q: How do I get my LinkedIn cookies?** 1. Open **Chrome** and go to [linkedin.com](https://www.linkedin.com). Make sure you're logged in. 2. Press **F12** (or right-click → Inspect) to open Developer Tools. 3. Go to the **Application** tab → **Cookies** → `https://www.linkedin.com`. 4. Find `li_at` and copy its **Value**. 5. Find `JSESSIONID` and copy its **Value** (it looks like `"ajax:123456789"`). 6. Paste them into the scraper input: ```json { "cookies": [ {"name": "li_at", "value": "paste_your_li_at_value_here"}, {"name": "JSESSIONID", "value": "paste_your_jsessionid_value_here"} ] } ``` > **Tip:** You can also use a browser extension like [EditThisCookie](https://chromewebstore.google.com/detail/editthiscookie) to export all cookies at once as JSON. **Q: How often do cookies expire?** A: LinkedIn cookies typically last several weeks, but they can expire sooner if you log out or if LinkedIn detects unusual activity. Re-export them when needed. **Q: Can I use this without cookies?** A: No. LinkedIn events require authentication to access full details. The cookies provide your authenticated session. **Q: What is the difference between keyword search and URL scraping?** A: Keyword search finds events matching your query across LinkedIn (up to 100 results). URL scraping fetches full details from specific event pages you already know about. **Q: Why are some fields empty in the results?** A: Not all events have all fields populated. For example, online events won't have a venue address, and not all events list speakers or hashtags. ### 📬 Support We're building this scraper for **you**, your feedback makes it better for everyone! - 💡 **Need a feature?** Tell us what's missing and we'll prioritize it - ⚙️ **Custom solutions**: Contact us for enterprise integrations or high-volume needs We respond to every message, usually within 24 hours. Don't hesitate, even small suggestions help! Check out our other scrapers: [silentflow on Apify](https://apify.com/silentflow) # Actor input Schema ## `cookies` (type: `array`): Your LinkedIn cookies exported from browser. Must include 'li\_at' and 'JSESSIONID'. Use a browser extension like EditThisCookie to export them as JSON. ## `keywords` (type: `array`): Keywords to search for LinkedIn events (e.g., 'AI conference', 'tech meetup'). Each keyword triggers a separate search. ## `eventUrls` (type: `array`): Direct LinkedIn event URLs to scrape. Format: https://www.linkedin.com/events/event-name-123456789 ## `limit` (type: `integer`): Maximum total number of events to return ## `userAgent` (type: `string`): Custom User-Agent string. Leave empty for automatic Chrome UA rotation. ## `proxy` (type: `object`): Select proxies to be used. Residential proxies recommended. ## Actor input object example ```json { "cookies": [ { "name": "li_at", "value": "YOUR_LI_AT_COOKIE_HERE" }, { "name": "JSESSIONID", "value": "YOUR_JSESSIONID_HERE" } ], "keywords": [ "AI conference" ], "eventUrls": [], "limit": 50, "userAgent": "", "proxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # Actor output Schema ## `events` (type: `string`): Complete event data including: title, description, url, startDateISO, endDateISO, eventType (online/in-person), location, city, country, organizerName, organizerProfileUrl, numAttendees, coverImage, hashtags. ## `eventsCSV` (type: `string`): CSV format export of all events for spreadsheet analysis ## `eventsExcel` (type: `string`): Excel format export of all events # 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 = { "cookies": [ { "name": "li_at", "value": "YOUR_LI_AT_COOKIE_HERE" }, { "name": "JSESSIONID", "value": "YOUR_JSESSIONID_HERE" } ], "keywords": [ "AI conference" ], "eventUrls": [] }; // Run the Actor and wait for it to finish const run = await client.actor("silentflow/linkedin-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 = { "cookies": [ { "name": "li_at", "value": "YOUR_LI_AT_COOKIE_HERE", }, { "name": "JSESSIONID", "value": "YOUR_JSESSIONID_HERE", }, ], "keywords": ["AI conference"], "eventUrls": [], } # Run the Actor and wait for it to finish run = client.actor("silentflow/linkedin-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 '{ "cookies": [ { "name": "li_at", "value": "YOUR_LI_AT_COOKIE_HERE" }, { "name": "JSESSIONID", "value": "YOUR_JSESSIONID_HERE" } ], "keywords": [ "AI conference" ], "eventUrls": [] }' | apify call silentflow/linkedin-events-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=silentflow/linkedin-events-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Linkedin Events Scraper", "description": "Scrape LinkedIn events with full authenticated access. Search by keywords or fetch specific event URLs. Extract titles, descriptions, dates, locations, organizers, attendee counts, speakers, and more. Ideal for sales prospecting, recruiting, market research, and competitive event analysis.", "version": "1.0", "x-build-id": "4gZ3TAflXmMbdLdSd" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/silentflow~linkedin-events-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-silentflow-linkedin-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/silentflow~linkedin-events-scraper/runs": { "post": { "operationId": "runs-sync-silentflow-linkedin-events-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/silentflow~linkedin-events-scraper/run-sync": { "post": { "operationId": "run-sync-silentflow-linkedin-events-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "cookies" ], "properties": { "cookies": { "title": "LinkedIn Cookies", "type": "array", "description": "Your LinkedIn cookies exported from browser. Must include 'li_at' and 'JSESSIONID'. Use a browser extension like EditThisCookie to export them as JSON." }, "keywords": { "title": "Search Keywords", "type": "array", "description": "Keywords to search for LinkedIn events (e.g., 'AI conference', 'tech meetup'). Each keyword triggers a separate search.", "items": { "type": "string" } }, "eventUrls": { "title": "Event URLs", "type": "array", "description": "Direct LinkedIn event URLs to scrape. Format: https://www.linkedin.com/events/event-name-123456789", "items": { "type": "string" } }, "limit": { "title": "Maximum events", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum total number of events to return", "default": 50 }, "userAgent": { "title": "User Agent", "type": "string", "description": "Custom User-Agent string. Leave empty for automatic Chrome UA rotation.", "default": "" }, "proxy": { "title": "Proxy configuration", "type": "object", "description": "Select proxies to be used. Residential proxies recommended.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "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 } } } } } } } } } } ```