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 readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description confirms it's a read operation and adds specific return fields, which is useful but not substantial 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?
The description is concise with two sentences. The first sentence states the core purpose, and the second provides usage guidance. No extraneous content.
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 (one optional parameter, no output schema), the description adequately covers purpose, return fields, and usage. It could mention pagination or limits, but is already fairly complete.
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 schema already documents the include_inactive parameter. The description does not add any additional meaning to the parameter, so baseline 3 applies.
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 ('List'), resource ('subscriptions'), and scope ('caller's active'). It also lists the exact fields returned (id, type, params, etc.), distinguishing it from sibling tools like subscribe and unsubscribe.
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 explicit use cases: 'review what you're monitoring before adding more or to find an id to cancel.' This guides when to use the tool, though it doesn't explicitly exclude alternatives.
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 overlap heavily: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical variants; entity_profile, compare_entities, recent_changes, and deep_research have overlapping research scopes; and the six Polymarket tools cover similar ground. Individual descriptions are detailed, but an agent could easily select the wrong meta-tool.
Nearly all names use snake_case, which is readable, but the pattern is inconsistent: some are verb_noun (resolve_entity, list_subscriptions), some are bare noun phrases (entity_profile, polymarket_edges, recent_changes), and memory tools are single verbs (remember, recall, forget). There is no predictable naming convention across the set.
32 tools is already at the heavy end, but the real problem is scope mismatch: a server named 'Cnpj Br' dedicates 31 of 32 tools to Pipeworx data research, prediction markets, memory, and web utilities, with only a single CNPJ lookup. The count feels bloated and incoherent for the apparent purpose.
For the stated CNPJ/Brazil domain, the entire surface is one lookup tool: no search by company name, no CNAE/industry breakdowns, no batch or comparative lookups, and no related Brazil KYB data. As a CNPJ-focused server it is severely incomplete.