webdata-tools-mcp

Find upcoming events (Luma, Eventbrite, Meetup)

find_events

Read-onlyIdempotent

Find upcoming events by topic and city or from Luma, Eventbrite, and Meetup links, returning structured details on dates, venues, organizers, tickets, and attendance for prospecting and research.

Instructions

Upcoming events by topic and city, or from Luma / Eventbrite / Meetup links (or any page with schema.org events): name, dates, venue with address and coordinates, organiser, hosts, ticket prices, free/sold-out and attendee count, in one format. Use for event prospecting, sponsorships and community research. Runs the Apify Actor tacps126/events-scraper on your Apify account (about $0.001 per event; spend per call is capped at $0.5).

Input Schema

Name	Required	Description
`urls`	No	Luma city/category/calendar/event links, Eventbrite searches or events, Meetup search or group links, or any events page.
`sources`	No	Sites searched for `searches` (default all three). Meetup knows about 70 big cities by name; others as "City, CC" (e.g. "Lyon, FR").
`location`	No	City in plain words (e.g. "London", "Bengaluru") or "online". Luma searches within a city.
`searches`	No	Topics or keywords, e.g. ["AI","startup"].
`max_items`	No	Maximum results to return (default 30, max 500). Cost scales with this.
`extra_input`	No	Advanced: extra Actor input fields, merged over the defaults.
`include_details`	No	Open each event for organiser, tickets and full description. Off = faster.

Output Schema

Name	Required	Description
`tool`	Yes	Name of the tool that produced the result.
`count`	Yes	Number of records the Actor returned.
`items`	Yes	The records. Long text fields are shortened to 600 characters.
`shown`	Yes	Number of records included in `items` (can be lower than count when the result is long).
`truncated`	Yes	True when records were left out to keep the result short; ask for fewer items.

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedv0.10.1Oct 23, 2026

changedInput schema / properties / sources / description

Previous value: -"Sites searched for `searches` (default both). Meetup works through links."New value: +"Sites searched for `searches` (default all three). Meetup knows about 70 big cities by name; others as \"City, CC\" (e.g. \"Lyon, FR\")."

changedInput schema / properties / sources / items / enum

Previous value: -[
-  "luma",
-  "eventbrite"
-]New value: +[
+  "luma",
+  "eventbrite",
+  "meetup"
+]

Addedv0.5.0Oct 21, 2026

TDQS

A4.5/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare this as read-only, open-world, idempotent, and non-destructive. The description adds meaningful operational context beyond that: it runs the Apify Actor tacps126/events-scraper on the user’s Apify account, costs about $0.001 per event, and caps spend at $0.5 per call. It stops short of covering auth setup or failure modes, but the paid external dependency and cost cap are important disclosures.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose and stays to three sentences. The long field list in the first sentence earns its place by clarifying output breadth, and the use-case and cost sentences add actionable context with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a seven-parameter tool with a nested extra_input object and an output schema, the description covers the important context: input modes, supported sources, return content, intended use cases, and the paid actor cost model. Remaining schema-level details are already documented in structured fields.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already carries most parameter detail. The description still adds useful meaning by clarifying the two input modes—topic/city search versus URL/link scraping—and by tying cost to per-event pricing, which helps an agent choose max_items and sourcing parameters appropriately.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb and resource: it finds upcoming events by topic/city or from Luma, Eventbrite, Meetup, or schema.org event pages. It also lists the returned fields (dates, venue, organiser, prices, attendance), making the tool clearly identifiable against the job/news/Reddit-oriented siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives clear usage contexts: event prospecting, sponsorships, and community research. It does not explicitly state when not to use the tool or name alternative event tools, but the intended scenarios are well framed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.