Skip to main content
Glama

Ticketmaster

by io.github.pipeworx-io

Recent Alerts

recent_alerts
Read-onlyIdempotent

Pull fired events from your subscription feed. Returns the most recent alerts the evaluator has written to your persisted feed — each carries source, citation_uri (pipeworx:// when available), and the raw event payload. Filter by type (e.g. "sec_8k") and/or since (ISO timestamp). Set mark_read:true to flag returned events read so the next call only shows newer ones. Polls work fine; the same feed is also at GET registry.pipeworx.io/alerts.json for scripts and dashboards.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoOptional — filter to one subscription type.
limitNoMax events to return (1-200, default 50).
sinceNoOptional ISO timestamp — return events fired_at >= this time.
mark_readNoFlag the returned events read in the same call (default false).
unread_onlyNoReturn only events where read_at is null (default false).

Schema Changelog

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

  1. Added

TDQS

A3.7/5.0
Behavior1/5

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

Annotation Contradiction: The description discloses a state-changing side effect ('Set mark_read:true to flag returned events read so the next call only shows newer ones'), which directly contradicts the readOnlyHint: true annotation. This makes the behavioral profile misleading despite the description's transparency.

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 relatively concise and front-loaded with the main action. It includes useful extras like the alternative HTTP endpoint without being wordy. Every sentence serves a purpose, though the HTTP endpoint could be considered a minor digression.

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?

For a moderate-complexity tool with no output schema, the description covers the return payload, filtering, mark_read behavior, and polling. It provides sufficient context for an agent to use the tool effectively, though the contradiction with annotations slightly undermines completeness.

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?

The schema already covers 100% of parameters, so the baseline is 3. The description adds semantic value by explaining the purpose of type ('sec_8k') and since (ISO timestamp), and by detailing the side effect of mark_read, going beyond simple parameter definitions.

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 opens with a specific verb and resource: 'Pull fired events from your subscription feed.' It clearly states what the tool does and distinguishes it by mentioning the persisted feed and evaluator-written alerts, setting it apart from other tools like recent_changes or event_search.

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 says 'Polls work fine' and offers an alternative HTTP endpoint for scripts/dashboards, which implies usage scenarios. It also explains filtering by type and since, giving practical context. However, it does not explicitly name sibling tools or state when not to use this tool.

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