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Get Luma Events

get_luma_events
Read-only

Fetches every page (no truncation), so the returned list is the complete calendar — upcoming and past events alike. Use it to answer "which event is next", to find an event's id for get_luma_guests, or when a luma_event_created trigger fires and you need the full event context. Dict with events array and count. Each event dict is Luma's event object, the useful fields being: id (starts with "evt-", the key get_luma_guests takes), name, start_at / end_at (ISO 8601 UTC), timezone (IANA), url (the lu.ma page), location_type, meeting_url, visibility, registration_open, require_approval, spots_remaining, description_md.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
on_behalf_ofNoAn agency client's email, from list_agency_clients, to run this call in that client's account: their agents, settings, connected accounts, and credits. Omit it to act on your own account.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / on_behalf_of
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "string"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "description": "An agency client's email, from list_agency_clients, to run this call in that client's account: their agents, settings, connected accounts, and credits. Omit it to act on your own account."
      +}
  2. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Beyond the readOnlyHint=true annotation, the description discloses pagination behavior ('Fetches every page (no truncation)'), result ordering, and that both upcoming and past events are included — meaningful behavioral context an agent cannot infer from the annotation alone.

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

Conciseness4/5

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

Front-loads purpose in the summary and separates return details into a dedicated block. The field list in returns is long but earns its place given there is no output schema to document the shape.

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

Completeness4/5

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

With no output schema, the description carries the return-value burden and does so thoroughly, enumerating event fields (id, name, start_at/end_at, spots_remaining, etc.). Purpose, usage, and returns are all covered; only explicit when-not-to-use guidance is missing.

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

Parameters3/5

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

Schema description coverage is 100%; the single on_behalf_of parameter is fully documented in the schema (agency client email, sourced from list_agency_clients, omit for own account). The description adds nothing beyond the schema, so the baseline 3 applies.

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?

States a specific verb and resource ('List all events on the user's Luma calendar') with ordering ('most recent first') and scope ('complete calendar — upcoming and past'). It explicitly relates itself to the get_luma_guests sibling by supplying the event id that sibling consumes, so an agent can place it in the tool graph.

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?

Gives three concrete when-to-use cases: answering 'which event is next', sourcing an id for get_luma_guests, and supplying context after a luma_event_created trigger. It does not name a when-not-to-use condition or an alternative list tool, but the positive routing is clear and actionable.

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

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