unsubscribeCancel a subscription by id. Ownership is enforced — you can only cancel your own subscriptions. The row is deactivated (not deleted) so its historical events stay available via recent_alerts.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Subscription id (uuid) returned by subscribe. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations, the description discloses key behaviors: ownership enforcement ('you can only cancel your own subscriptions') and the non-destructive nature ('row is deactivated (not deleted)'). This adds significant value beyond the annotations' readOnly=false and destructiveHint=false, clarifying exactly what happens without contradicting them.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise sentences, each adding necessary context: the action, ownership constraint, and soft-delete behavior. It is front-loaded with the verb and resource, and every sentence earns its place without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple mutation tool with one parameter, the description covers the essential facets: what it does, side effects, and ownership conditions. The pointer to recent_alerts provides a complete picture for the agent to select and invoke the tool correctly. No output schema is present, so no return-value explanation is required.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the id parameter is well-described in the schema as 'Subscription id (uuid) returned by subscribe.' The description does not add further parameter details, which is acceptable because the schema fully defines the only parameter. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Cancel a subscription by id.' This is a specific verb (cancel) with a resource (subscription). It also distinguishes from siblings by noting the soft-delete behavior and referencing recent_alerts for historical events, making its role in the subscription lifecycle unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides contextual guidance: it can only cancel the user's own subscriptions and that deactivation preserves historical events accessible via recent_alerts. This implies the appropriate use case (when you want to stop alerts but retain data), though it doesn't explicitly name alternatives like list_subscriptions or subscribe for other actions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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 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.
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.
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.