Skip to main content
Glama

Ticketmaster

by io.github.pipeworx-io

Attraction Search

attraction_search
Read-onlyIdempotent

Ticketmaster Discovery API — search attractions (artists, sports teams, performers) by keyword, classificationName, or other filters. Returns attraction name, ID, classifications, and images.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo0-based page number. Deep paging is capped at page × size ≤ 1000.
sizeNoResults per page (default 20).
sortNoSort order. Ticketmaster accepts only these values for attractions; anything else is a 400.
keywordNoArtist, team or performer name, e.g. "Taylor Swift". Omitting it returns Ticketmaster's default attraction feed, not a search.
countryCodeNo2-letter country code, e.g. "US".
classificationNameNoSegment/genre, e.g. "Music", "Sports".

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed3 schema fields changed
    • changedInput schema / properties / page / description
      Previous value: -"0-based page number."New value: +"0-based page number. Deep paging is capped at page × size ≤ 1000."
    • changedInput schema / properties / sort / description
      Previous value: -"Sort order, e.g. \"relevance,desc\"."New value: +"Sort order. Ticketmaster accepts only these values for attractions; anything else is a 400."
    • addedInput schema / properties / sort / enum
      Added value: +[
+  "name,asc",
+  "name,desc",
+  "relevance,asc",
+  "relevance,desc",
+  "random"
+]
  2. Changed6 schema fields changed
    • addedInput schema / properties / classificationName
      Added value: +{
+  "description": "Segment/genre, e.g. \"Music\", \"Sports\".",
+  "type": "string"
+}
    • addedInput schema / properties / countryCode
      Added value: +{
+  "description": "2-letter country code, e.g. \"US\".",
+  "type": "string"
+}
    • addedInput schema / properties / keyword
      Added value: +{
+  "description": "Artist, team or performer name, e.g. \"Taylor Swift\". Omitting it returns Ticketmaster's default attraction feed, not a search.",
+  "type": "string"
+}
    • addedInput schema / properties / page
      Added value: +{
+  "description": "0-based page number.",
+  "type": "number"
+}
    • addedInput schema / properties / size
      Added value: +{
+  "description": "Results per page (default 20).",
+  "type": "number"
+}
    • addedInput schema / properties / sort
      Added value: +{
+  "description": "Sort order, e.g. \"relevance,desc\".",
+  "type": "string"
+}
  3. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, so the safety profile is covered. The description adds the specific API source (Ticketmaster Discovery API) and the return fields, which provides additional behavioral context. It does not disclose any non-obvious behaviors (like rate limits or pagination), but given the annotations, the bar is lower. The description is consistent with annotations and adds a bit of value.

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?

The description is a single, well-structured sentence that front-loads the purpose and includes the key filter types and return fields. It avoids redundancy and is easy to parse. A slightly more concise phrasing (e.g., removing 'or other filters') would earn a 5, but this is already efficient and informative.

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?

Given the tool has 6 parameters with rich schema descriptionsasi, the description adequately covers the core purpose, typical inputs, and expected outputs. It doesn't mention pagination limits or sorting restrictions, but those are in the parameter descriptions. The description is sufficient for an agent to decide whether to invoke this tool for a given query.

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?

The input schema provides detailed descriptions for all six parameters (e.g., '0-based page number', '2-letter country code'), so schema coverage is high. The description only reiterates the existence of keyword and classificationName without adding new semantics beyond what the schema already explains. Per the rubric, baseline 3 is appropriate when the schema carries the semantic weight.

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 clearly states the tool's purpose: searching attractions (artists, sports teams, performers) via the Ticketmaster Discovery API. It explicitly names the primary filter (keyword, classificationName) and the output fields (name, ID, classifications, images), making it easy for an agent to distinguish from sibling search tools like venue_search or event_search. The verb 'search' plus the resource 'attractions' is specific and unambiguous.

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?

The description provides context about what the tool does and mentions the types of entities (artists, teams, performers) which implies it is for attractions, not venues or events. However, it does not explicitly state when to use this tool over alternatives, such as venue_search or event_search, nor any exclusions (e.g., 'for venues use venue_search'). Given the clear naming and sibling context, the guidance is adequate but not explicit.

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

All Ticketmaster toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

C2.9/5.0
Disambiguation2/5

The tools fall into two unrelated domains (Ticketmaster event discovery and Pipeworx data research), and within the Pipeworx set there are near-duplicate tools like ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded, plus multiple overlapping prediction-market tools (polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, etc.). An agent would struggle to choose among these overlapping options and may not realize that most tools are unrelated to the server's stated name.

Naming Consistency3/5

Naming uses consistent snake_case, but the pattern is mixed: Ticketmaster resource fetchers are bare nouns (event, venue, attraction, classification) while search tools use verb_noun (event_search, venue_search). Pipeworx tools vary between verb phrases (ask_pipeworx, validate_claim) and descriptive noun phrases (entity_profile, polymarket_kalshi_spread). This inconsistency makes predicting tool names harder, though each name is still readable.

Tool Count2/5

41 tools is excessive for a server titled 'Ticketmaster' when only about 10 are Ticketmaster-related; the other 30 cover an entirely different service (Pipeworx). The count is far beyond a focused scope and suggests the server should be split into two separate, well-scoped MCP servers.

Completeness4/5

For the Ticketmaster half, the surface is complete for read-only event discovery (search events/venues/attractions, get single resources, classifications, autocomplete). For the Pipeworx half, the tool suite is extensive, covering lookup, research, prediction markets, memory, subscriptions, and feedback. The only notable gap is the lack of any write operations, but this is consistent with the read-only nature of the underlying APIs.

Resources