A Model Context Protocol server for discovering events, venues, and attractions through the Ticketmaster Discovery API
Single tool with complete JSON Schema, clear verb naming, and descriptive parameters. However, output schema is undocumented, descriptions could be more actionable, and no error handling guidance. The tool follows basic patterns but lacks production-grade depth.
Search for events, venues, or attractions on Ticketmaster
No documented output schema. LLMs cannot plan downstream actions or extract needed fields. Rubric requires 'Document the output schema' and 'Return structured objects with typed fields.'
Tool description lacks context on WHEN to use it vs alternatives, WHAT it returns, and any prerequisites. Current: 'Search for events, venues, or attractions on Ticketmaster' (68 chars). Actionable description should be 50-200 chars with use-case guidance.
No error handling or recovery guidance. Tool will fail on invalid dates, missing API key, or rate limits, but provides no actionable error messages. Rubric: 'Error responses must tell the LLM what to do next.'
Parameter 'format' enum defaults to 'json' but no documentation of actual output fields. LLM cannot know if results include price, date, venue_id, or other critical chaining data.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | D | 57 | 2026-07-28+ | v2 |
| 2026-03-09 | C | 60 | - | v1 |
No pagination or result limits documented. If 'Music' search returns 500+ events, tool could exhaust context window. Rubric: 'cap results at a reasonable limit (e.g. 20-50) and offer pagination.'
Parameter descriptions are minimal (e.g., 'City name', 'State code'). No guidance on format, constraints, or mutual exclusivity. LLM cannot infer whether city is required with stateCode, or if countryCode changes behavior.