list_subscriptionsList the caller's active subscriptions. Returns id, type, params, created_at, last_fired_at, fire_count for each. Use this to review what you're monitoring before adding more or to find an id to cancel.
| Name | Required | Description | Default |
|---|---|---|---|
| include_inactive | No | Include cancelled subscriptions in the response (default false). |
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?
Annotations already declare readOnly, idempotent, and non-destructive. The description adds that only active subscriptions are returned by default and includes the option to include inactive. It also enumerates the response fields, which is useful behavioral context beyond the annotations.
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?
Two sentences, front-loaded with the core purpose, followed by return fields and usage guidance. Every sentence earns its place with no redundancy or fluff.
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?
With one optional parameter, no output schema, and strong annotations, the description provides the necessary return fields and default filtering behavior. It fully equips the agent to decide when and how to invoke the tool.
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 single parameter include_inactive is already fully described in the schema ('Include cancelled subscriptions in the response (default false)'). With 100% schema coverage, the description adds little parameter-level value beyond reinforcing the default behavior.
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 states 'List the caller's active subscriptions' with a specific verb, resource, and scope. It also names the exact fields returned (id, type, params, created_at, last_fired_at, fire_count), clearly distinguishing it from sibling tools like subscribe/unsubscribe by referencing the purpose of reviewing before adding or canceling.
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?
Provides clear usage context: 'Use this to review what you're monitoring before adding more or to find an id to cancel.' This implies when to use relative to subscribe/unsubscribe, though it does not explicitly name alternatives or state when not to use.
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 occupy blurred boundaries: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all route questions to overlapping data pipelines, and the Polymarket family (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, polymarket_kalshi_spread) heavily overlaps in purpose. Individual descriptions are detailed, but an agent must read long text to avoid misselection, especially when the three anime-quote tools are surrounded by unrelated tool families.
Most tools use snake_case and many begin with verbs (ask_, search_, resolve_, scan_, compare_, validate_), but several are noun-first or noun-phrase names like entity_profile, bet_research, random_quote, recent_alerts, recent_changes, and pipeworx_trending. There is no chaotic camelCase/snake_case mix, but the convention is not applied consistently enough for a predictable pattern.
34 tools is heavy for any single-purpose server, and the vast majority have nothing to do with anime quotes—they are Pipeworx data tools, prediction-market tools, subscription tools, memory tools, and AI-audit tools. For a server named animequotes, only random_quote, search_by_anime, and search_by_character fit the stated purpose, making the count wildly disproportionate.
For the apparent anime-quote domain, random_quote, search_by_anime, and search_by_character cover basic lookup but leave notable gaps: no search by quote text, no quote-by-id fetch, no ability to list all series or characters, and no pagination or metadata browsing. The unrelated tools do not fill these gaps, so the anime-quote surface is functional but incomplete.