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?
The description discloses key behavioral traits beyond annotations: ownership enforcement ('you can only cancel your own subscriptions') and non-destructive deactivation ('The row is deactivated (not deleted) so its historical events stay available via recent_alerts'). These align with destructiveHint=false and add context.
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 two sentences, front-loaded with the action and then constraints. No unnecessary words.
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 one-parameter mutation tool with no output schema, the description covers the important side effects: deactivation and preservation of historical events. It does not specify return values or error cases, but annotations provide idempotency and open-world hints.
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?
The schema covers the id parameter fully (100% coverage) with a description referencing subscribe. The tool description adds the ownership constraint that the id must belong to the caller, which adds meaning beyond the schema.
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 action: 'Cancel a subscription by id.' It uses a specific verb and resource, and it distinguishes from siblings like subscribe and list_subscriptions by specifying the cancellation semantics.
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 implies when to use (when you want to cancel a subscription) but does not explicitly compare to alternatives. It mentions ownership enforcement, which is a constraint, but does not say 'use this instead of list_subscriptions' or similar.
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.
Several tools have unclear boundaries: ask_pipeworx and ask_pipeworx_beta are explicitly identical in behavior today, while discover_tools and suggest_questions overlap as discovery/onboarding entry points. The Polymarket tools also blur together across arbitrage, edges, edge tracking, and fill risk, making tool selection prone to mistakes despite long descriptions.
Names are consistently lowercase snake_case and readable, but they mix conventions: some are clear verb_noun actions like validate_claim and compare_entities, while others are noun-led like recent_alerts and entity_profile, or domain-prefixed like polymarket_edges and opensensemap_nearby. There is no single predictable naming pattern across the set.
At 34 tools, this exceeds the 25+ threshold for a heavy tool set, and the tools span several unrelated domains: OpenSenseMap sensors, Pipeworx data access, Polymarket research, memory, subscriptions, and AI visibility. A server named Opensensemap hosting this much unrelated functionality feels poorly scoped.
The OpenSenseMap portion covers nearby discovery, box lookup, and area averages, but lacks historical/time-series access and station lifecycle operations, which are notable gaps for a sensor data server. The broader Pipeworx surface has strong lookup, research, validation, and subscription coverage, so the main incompleteness is in the named domain.