# Luma Event & Attendee Scraper - Cheapest (`doin2much/luma-attendee-scraper`) Actor Scrape hosted Luma events and full guest/attendee lists (email, LinkedIn, X/Twitter, Instagram, TikTok, YouTube, website, phone, bio, registration answers, check-in status) using a host session cookie. - **URL**: https://apify.com/doin2much/luma-attendee-scraper.md - **Developed by:** [Neel Majmudar](https://apify.com/doin2much) (community) - **Categories:** Automation, Lead generation, Business - **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: 5.00 out of 5 stars ## 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ### What does Luma Event & Attendee Scraper do? **Luma Event & Attendee Scraper** scrapes **hosted events** and their **full guest / attendee lists** from [Luma](https://lu.ma) using a host session cookie. It calls Luma’s private JSON API (`api.lu.ma`) — the same surfaces as the host dashboard — so you get event metadata **plus** rich attendee profiles: email, phone, bio, **LinkedIn, X/Twitter, Instagram, TikTok, YouTube, website**, location, RSVP/check-in status, UTM/referral, and registration answers. Runs on the [Apify](https://apify.com) platform with scheduling, monitoring, API access, and integrations. ### Why use Luma Event & Attendee Scraper? - Export full attendee CRM lists (email + socials) from events you host - Sync hosted event catalogs and guest status counts into spreadsheets or pipelines - Backfill past events and monitor upcoming ones on a schedule - Avoid browser automation: authenticated HTTP only (fast and predictable) ### How to use Luma Event & Attendee Scraper 1. Open the Actor in [Apify Console](https://console.apify.com). 2. Paste your Luma host session cookie into **Luma session cookie** (`sessionCookie`). 3. Leave **Include attendees** on (default) to scrape guest lists with socials. Optionally keep **Include guest status counts** on for approved/waitlist/checked-in breakdowns. 4. Choose **Event period** (`all`, `past`, or `future`). Use **Max events** while testing. 5. Click **Start**. Raise **Max total charge USD** if you need more than ~500 attendees (platform default is often ~$5 ≈ 1 event + ~495 attendees at $0.01 each). 6. Open **Output**: **Attendees** (default dataset) and **Events** (separate dataset). Storage → Dataset dropdown also lists both. #### How to get the Luma session cookie 1. Sign in to [lu.ma](https://lu.ma) with a **host** account. 2. Open DevTools → Application (or Storage) → Cookies → `lu.ma`. 3. Copy the value of `luma.auth-session-key`. 4. Paste the raw value **or** `luma.auth-session-key=...` into `sessionCookie`. Sessions expire. A 401 means refresh the cookie; a 403 usually means the cookie is not a host/admin session. ### Input | Field | Type | Required | Default | Description | | --- | --- | --- | --- | --- | | `sessionCookie` | string (secret) | yes | — | Raw `luma.auth-session-key` or full cookie string | | `period` | enum | no | `all` | `all`, `past`, or `future` | | `maxEvents` | integer | no | `0` | Cap on events (`0` = no cap) | | `maxAttendeesPerEvent` | integer | no | `0` | Cap attendees scraped per event (`0` = no cap); stops guest pagination early | | `maxAttendees` | integer | no | `0` | Cap total attendees across the whole run (`0` = no cap) | | `includeGuestCounts` | boolean | no | `true` | Nested `guestCounts` status breakdown on event rows | | `includeGuests` | boolean | no | `true` | Emit one attendee dataset row per guest (billed per row) | #### Example input ```json { "sessionCookie": "YOUR_LUMA_AUTH_SESSION_KEY", "period": "all", "maxEvents": 0, "maxAttendeesPerEvent": 500, "maxAttendees": 5000, "includeGuestCounts": true, "includeGuests": true } ```` ### Output Events and attendees are stored in **separate datasets** (Apify views cannot filter a mixed dataset by `recordType`): | Dataset | PPE charge | Meaning | | --- | --- | --- | | **Events** (`events`) | `event-scraped` (**$0.01** each) | One row per hosted event (metadata + counts; no nested guests) | | **Attendees** (`default`) | `attendee-scraped` (**$0.01** each / $10 per 1,000) | One row per guest with email/socials/status + parent event fields | Example: 1 event + 495 attendees ⇒ **$4.96** PPE (plus a tiny actor-start fee). As the **Actor owner**, Console may show only platform compute (~$0.02) because your own runs are not billed for PPE — check the run’s `chargedEventCounts` to verify event/attendee charges. #### Example event row ```json { "recordType": "event", "lumaApiId": "evt-xxxxxxxx", "lumaUrl": "your-event-slug", "name": "Founder meetup", "coverImageUrl": "https://images.lumacdn.com/...", "address": "123 Market St, San Francisco, CA", "city": "San Francisco", "country": "United States", "countryCode": "US", "descriptionShort": "An evening for founders", "startAt": "2026-07-20T18:00:00+00:00", "endAt": "2026-07-20T21:00:00+00:00", "timezone": "America/Los_Angeles", "guestCountApproved": 42, "guestCounts": { "approved": 42, "checkedIn": 30, "declined": 2, "invited": 10, "joinedOnline": 0, "notCheckedIn": 12, "pendingApproval": 0, "session": 0, "waitlist": 5 }, "scrapedAttendeeCount": 42 } ``` #### Example attendee row ```json { "recordType": "attendee", "eventName": "Founder meetup", "eventLumaApiId": "evt-xxxxxxxx", "eventLumaUrl": "your-event-slug", "eventStartAt": "2026-07-20T18:00:00+00:00", "eventCity": "San Francisco", "eventCountry": "United States", "lumaGuestApiId": "gst-xxxxxxxx", "lumaUserApiId": "usr-xxxxxxxx", "email": "alex@example.com", "name": "Alex Founder", "firstName": "Alex", "lastName": "Founder", "phone": "+1…", "avatarUrl": "https://…", "bio": "Building something new", "linkedinHandle": "in/alexfounder", "twitterHandle": "alexfounder", "instagramHandle": null, "tiktokHandle": null, "youtubeHandle": null, "website": "https://example.com", "city": "San Francisco", "country": "United States", "locale": "en-US", "approvalStatus": "approved", "registeredAt": "2026-06-01T18:00:00+00:00", "registeredOrCreatedAt": "2026-06-01T18:00:00+00:00", "checkedInAt": null, "lastCheckedInAt": null, "invitedAt": null, "joinedAt": null, "hasJoinedEvent": false, "declineMessage": null, "utmSource": "newsletter", "referredByUserApiId": null, "registrationAnswers": [] } ``` If a run scrapes 10 events and 2,000 attendees, the dataset has **2,010 items** and billing is approximately `(10 × $0.01) + (2,000 × $0.01) = $20.10` plus the Actor start event. ### Attendee schema (emphasized) Every **attendee** dataset row includes these Luma admin guest-list fields: | Field | Description | | --- | --- | | `lumaGuestApiId` | Guest row id | | `lumaUserApiId` | Luma user id | | `email` / `name` / `firstName` / `lastName` | Identity | | `phone` / `avatarUrl` / `bio` | Contact & profile | | `linkedinHandle` | LinkedIn | | `twitterHandle` | X / Twitter | | `instagramHandle` | Instagram | | `tiktokHandle` | TikTok | | `youtubeHandle` | YouTube | | `website` | Personal / company site | | `city` / `country` / `locale` | Geo / locale | | `approvalStatus` | e.g. approved, pending\_approval, waitlist | | `registeredAt` / `registeredOrCreatedAt` / `invitedAt` / `joinedAt` | Lifecycle timestamps | | `checkedInAt` / `lastCheckedInAt` / `hasJoinedEvent` | Check-in / join | | `declineMessage` | Decline note when present | | `utmSource` / `referredByUserApiId` | Attribution | | `registrationAnswers` | Event-specific Q\&A (JSON array) | **Not included** (intentionally omitted, same as our internal product mapping): ticket purchase objects, pending revenue, crypto/web3 wallet fields, and Luma internal proxy keys. ### Event data table | Field | Description | | --- | --- | | `lumaApiId` | Luma event API id | | `lumaUrl` | Event URL slug | | `name` | Event title | | `startAt` / `endAt` | Schedule (ISO-8601) | | `city` / `country` / `countryCode` / `address` | Location | | `guestCountApproved` | Approved count from host role | | `guestCounts` | Optional status breakdown on **event** rows | | `scrapedAttendeeCount` | How many **attendee** rows were produced/charged for that event | | Attendee fields (`email`, socials, …) | On **attendee** rows only — see schema above | ### Pricing / Cost estimation How much does it cost to scrape Luma events and attendees? This Actor uses **pay-per-event (PPE)** pricing: | Charge event | Price | When charged | | --- | --- | --- | | `event-scraped` | **$0.01** per event | Each event dataset row | | `attendee-scraped` | **$0.01** per attendee ($10 / 1,000) | Each attendee dataset row | | `apify-actor-start` | Apify default (very low) | Actor run start (covers first seconds of compute) | Example: scrape 10 events with 2,000 total attendees → `(10 × $0.01) + (2,000 × $0.01) = $20.10` (plus the tiny start event), before any Store discounts. Use `maxAttendees` / `maxAttendeesPerEvent` to cap spend. HTTP-only scraping keeps platform usage low relative to these event charges. Set a **max total charge** on the run if you want a hard spending cap. ### Tips or Advanced options - Prefer `period: "future"` for recurring sync jobs. - Set `maxEvents` while testing before scraping multi-thousand guest lists (guest pages use ~1.2s delays). - Turn off `includeGuests` only when you need event metadata / counts without PII. - Cookie must be from a **host** account with admin access to the events. ### FAQ, disclaimers, and support **Is scraping Luma allowed?** Only scrape data you are authorized to access — typically **your own** hosted events. Respect Luma’s Terms of Service and privacy laws when handling guest PII. **Why 401?** Session expired — refresh `luma.auth-session-key`. **Why 403?** Not a host/admin cookie for those events. **Does this search public Luma events by keyword?** No. It lists **hosted** events for the authenticated host and their admin guest lists — not public keyword/location search. Open the Actor **Issues** tab for feedback, or ask about custom CRM / webhook integrations. # Actor input Schema ## `sessionCookie` (type: `string`): Your Luma auth session cookie. Paste the raw `luma.auth-session-key` value, or the full `luma.auth-session-key=...` cookie string. Must belong to a host account that can access admin guest lists. ## `period` (type: `string`): Which hosted events to fetch: past, future, or both (all). ## `maxEvents` (type: `integer`): Maximum number of hosted events to scrape. Use 0 for no cap. ## `maxAttendeesPerEvent` (type: `integer`): Maximum guest/attendee rows to scrape for each event. Use 0 for no per-event cap. Pagination stops early once the cap is reached. ## `maxAttendees` (type: `integer`): Maximum attendee rows to scrape across the whole run. Use 0 for no global cap. Useful for cost control when scraping many large events. ## `includeGuestCounts` (type: `boolean`): If true, adds nested `guestCounts` (approved, checkedIn, waitlist, invited, declined, etc.) from `/event/admin/get`. ## `includeGuests` (type: `boolean`): If true (recommended), scrapes attendees for each event into separate dataset rows (email, socials, status, etc.). Each attendee row is billed as attendee-scraped. ## Actor input object example ```json { "period": "all", "maxEvents": 0, "maxAttendeesPerEvent": 0, "maxAttendees": 0, "includeGuestCounts": true, "includeGuests": true } ``` # Actor output Schema ## `attendees` (type: `string`): Default dataset: one row per guest (attendee-scraped, $0.01 each). ## `events` (type: `string`): Separate dataset: one row per hosted event (event-scraped, $0.01 each). # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("doin2much/luma-attendee-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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("doin2much/luma-attendee-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 doin2much/luma-attendee-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=doin2much/luma-attendee-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Luma Event & Attendee Scraper - Cheapest", "description": "Scrape hosted Luma events and full guest/attendee lists (email, LinkedIn, X/Twitter, Instagram, TikTok, YouTube, website, phone, bio, registration answers, check-in status) using a host session cookie.", "version": "0.5", "x-build-id": "jv9IULRkaaUbqMJWj" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/doin2much~luma-attendee-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-doin2much-luma-attendee-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/doin2much~luma-attendee-scraper/runs": { "post": { "operationId": "runs-sync-doin2much-luma-attendee-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/doin2much~luma-attendee-scraper/run-sync": { "post": { "operationId": "run-sync-doin2much-luma-attendee-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "sessionCookie" ], "properties": { "sessionCookie": { "title": "Luma session cookie", "type": "string", "description": "Your Luma auth session cookie. Paste the raw `luma.auth-session-key` value, or the full `luma.auth-session-key=...` cookie string. Must belong to a host account that can access admin guest lists." }, "period": { "title": "Event period", "enum": [ "all", "past", "future" ], "type": "string", "description": "Which hosted events to fetch: past, future, or both (all).", "default": "all" }, "maxEvents": { "title": "Max events", "minimum": 0, "type": "integer", "description": "Maximum number of hosted events to scrape. Use 0 for no cap.", "default": 0 }, "maxAttendeesPerEvent": { "title": "Max attendees per event", "minimum": 0, "type": "integer", "description": "Maximum guest/attendee rows to scrape for each event. Use 0 for no per-event cap. Pagination stops early once the cap is reached.", "default": 0 }, "maxAttendees": { "title": "Max attendees (total)", "minimum": 0, "type": "integer", "description": "Maximum attendee rows to scrape across the whole run. Use 0 for no global cap. Useful for cost control when scraping many large events.", "default": 0 }, "includeGuestCounts": { "title": "Include guest status counts", "type": "boolean", "description": "If true, adds nested `guestCounts` (approved, checkedIn, waitlist, invited, declined, etc.) from `/event/admin/get`.", "default": true }, "includeGuests": { "title": "Include attendees (guest list)", "type": "boolean", "description": "If true (recommended), scrapes attendees for each event into separate dataset rows (email, socials, status, etc.). Each attendee row is billed as attendee-scraped.", "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 } } } } } } } } } } ```