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 provide readOnlyHint, idempotentHint, destructiveHint. The description adds that it returns specific fields and usage context, which is useful but not heavily beyond 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: first front-loads action and fields, second provides usage guidance. No wasted 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?
Given the tool's simplicity (1 optional parameter, no output schema, rich annotations), the description adequately covers purpose, return fields, and usage context.
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% with a single optional boolean parameter fully described. The description does not add extra meaning beyond the schema, earning the baseline score.
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 verb 'List' and resource 'caller's active subscriptions', and specifies returned fields. It distinguishes from sibling tools like subscribe/unsubscribe by mentioning review and cancellation use.
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 explicitly says 'Use this to review what you're monitoring before adding more or to find an id to cancel,' providing clear context for when to use the tool, though it doesn't explicitly 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.
Each tool has a clearly defined purpose with detailed descriptions, and despite some composite tools, there is no ambiguity in when to use which one.
Tool names mix verb_noun and noun_noun patterns, with some purely verb names, lacking a consistent convention. While readable, the pattern is not predictable.
With 23 tools, the server is on the heavy side for a mixed-purpose toolset. Each tool earns its place, but the count feels slightly bloated for the breadth of domains covered.
The server covers several domains (AI visibility, betting, entity lookup, etc.) with reasonable depth, but the lack of a unified domain means some areas feel under-served (e.g., no update/delete except memory).