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URL: https://apify.com/luis.pinto/events-finder/input-schema

⇱ Input · Events Finder: Luma, Eventbrite, Meetup Tech & AI Events · Apify

👁 Events Finder - Luma, Eventbrite & Meetup Tech Events avatar

Events Finder - Luma, Eventbrite & Meetup Tech Events

Pricing

from $5.70 / 1,000 events

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Events Finder - Luma, Eventbrite & Meetup Tech Events

Discover and rank tech, AI, and founder events across Luma, Eventbrite, and Meetup. LLM scores each event against your intent prompt and dedupes across scheduled runs. Export data, run via API, schedule and monitor runs, or integrate with other tools.

Pricing

from $5.70 / 1,000 events

Rating

0.0

(0)

Developer

👁 Luis Pinto

Luis Pinto

Maintained by Community

Actor stats

0

Bookmarked

16

Total users

10

Monthly active users

18 days ago

Last modified

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Cities

cities

Required

Cities the Actor scans on each source. Internally normalized to Luma city slugs, Eventbrite location paths, and Meetup location queries. Accepts common English names: 'Lisbon', 'Berlin', 'San Francisco', 'New York', 'London'. Trade-off: more cities means longer runs and more API credit consumed. Recommended: 1 to 3 cities per watch.

Type:array
Default:
[
"Lisbon"
]

Categories

categories

Required

Which event categories to scan. The Actor maps each category to the right filters per source (Eventbrite category IDs, Luma discovery tags, Meetup keywords), and the LLM uses them as priors when scoring relevance. Pick 1 to 3 to keep results focused. Selecting all dilutes scoring quality. Recommended: 'AI/ML' plus 'Founders/Startup' for tech founders.

Type:string[]
Default:
[
"AI/ML"
]

Date from

dateFrom

Optional

Earliest event start date the Actor will include, in ISO format (YYYY-MM-DD). Events starting before this date are dropped. Leave empty to default to today. Example: '2026-06-01'.

Type:string

Date to

dateTo

Optional

Latest event start date the Actor will include, in ISO format (YYYY-MM-DD). Events starting after this date are dropped. Leave empty to default to dateFrom plus 30 days. Recommended: a 14 to 60 day window. Narrower windows mean fewer false positives, wider windows surface high-value events earlier. Example: '2026-07-01'.

Type:string

Intent prompt

prompt

Required

Free-text description of the events you actually want to attend. The LLM scores each scraped event against this prompt and only events scoring above minScore are emitted. Be specific. Include audience, size, format, vibe. Example: 'AI engineering meetups with under 100 people where founders and senior engineers attend; prefer in-person evening events over webinars.'

Type:string

Your persona

persona

Optional

Who is attending. Used by the LLM as a prior alongside the prompt to weigh organizers and topics. Pick the closest match. The prompt always overrides. Recommended: 'Founder' for a company runner, 'Engineer' for IC eng meetups.

Type:string
Default:Generalist
Options:
GeneralistFounderEngineerPMMProductInvestorDesignerMarketer

Minimum relevance score

minScore

Optional

LLM relevance score below which events are dropped. The scorer rates each event 0 to 100 against the prompt and persona. Default 60 is a balanced threshold. Lower (40) for early discovery when you want to see more borderline events. Higher (80) for tight, high-signal Slack or Notion feeds.

Type:integer
Minimum:0
Maximum:100
Default:60

Max events per source

maxEventsPerSource

Optional

Per-source cap on how many events the Actor scrapes before scoring. Higher means more thorough discovery but longer runs and more credits consumed. Recommended: 50 for normal runs, 10 for cheap daily watches, 200 for one-off backfills.

Type:integer
Minimum:1
Maximum:500
Default:50

OpenRouter model

openRouterModel

Optional

OpenRouter model identifier used by the scorer. The Actor calls the public OpenRouter Apify Actor (sxck9mShRCfmMOZ8S) with this model. Cheaper models keep run costs near zero; smarter models produce better matchReasons. Recommended for Apify Store default: 'openai/gpt-4o-mini'. Other options: 'anthropic/claude-haiku-4-5', 'google/gemini-flash-1.5', 'meta-llama/llama-3.3-70b-instruct'.

Type:string
Default:openai/gpt-4o-mini

OpenRouter API key (optional)

openRouterApiKey

Optional

Optional OpenRouter API key. If set, the sub-Actor uses the user's own OpenRouter account and the LLM cost is billed directly (cheaper at scale). If empty, the sub-Actor's default billing applies. Check the OpenRouter Actor README for its current contract. Leave empty for the simplest setup.

Type:string

Dedup store name

dedupStoreName

Optional

Name of the named Key-Value Store used to remember which events have already been emitted. The Actor only emits events whose stable ID is not already in this store. Use different names for different watch profiles (for example 'events-lisbon-ai', 'events-berlin-founders'). Default fits most users.

Type:string
Default:events-finder-seen

Notion Connector (optional)

notionConnector

Optional

An Apify MCP Connector to the Notion workspace. When set, the Actor appends each new event as a row in a database under the page specified below. Create one in Apify Console > Settings > API & Integrations > MCP Connectors. Notion's MCP URL is either https://mcp.notion.com/mcp or https://api.notion.com/mcp. Apify injects the Notion credentials server-side. The Actor never sees a token. Leave empty to skip Notion sync.

Type:string | null

Notion parent page URL

notionParentPageUrl

Optional

URL of the Notion page where the events database lives. On the first run the Actor creates an 'Events Finder Inbox' database under this page. Subsequent runs append rows there. Share this page with the Apify integration (page menu > Connections > add the Apify integration). Example: https://www.notion.so/your-workspace/Events-Inbox-1a2b3c4d. Required when notionConnector is set.

Type:string

Max events per Notion sync

maxNotifyEvents

Optional

Hard cap on how many top-scored events to push to Notion per run. The dataset always contains all new events. This only limits writes to Notion. Notion handles hundreds of rows fine. The cap exists to keep run time predictable. Recommended: 50.

Type:integer
Minimum:1
Maximum:200
Default:50