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, idempotentHint, and destructiveHint, so the safety profile is clear. The description adds that by default only active subscriptions are listed and includes parameter description, but no additional behavioral traits beyond what annotations provide.
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 concise sentences: first states purpose and output fields, second gives usage guidance. 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 simple list tool with one optional parameter and no output schema, the description specifies return fields and usage context. Annotations cover safety. Complete for the complexity level.
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 clear description of the single parameter. The description does not add further 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 'List the caller's active subscriptions' with specific verb and resource, and lists the returned fields. It differentiates 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 advises using this tool to review existing subscriptions before adding more or to find an id to cancel, providing practical context for when to use it.
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.
Multiple tools overlap conceptually, e.g., ask_pipeworx / ask_pipeworx_beta / ask_pipeworx_grounded / deep_research all perform data retrieval, and bet_research / polymarket_edges / polymarket_arbitrage cover prediction markets with unclear boundaries. This overlap forces agents to carefully read descriptions to pick the right tool.
Naming is mostly snake_case but inconsistent in pattern: some are verb_noun (compare_entities), some are noun_verb (ai_visibility_check), and some are bare nouns (ipv4) or bare verbs (forget). While readable, the lack of a uniform pattern reduces predictability.
33 tools is high for a single server, especially given the server name 'Ipify' which implies a simple IP lookup service. The broad range (from memory ops to prediction market analysis) suggests the tool set is a collection of utilities rather than a coherent, scoped API.
The tool set lacks focus: for a server named 'Ipify', basic IP geolocation or ASN lookup is missing. As a general toolkit, it covers many areas superficially but has significant gaps (e.g., no tools for updating or deleting data, no domain-specific lifecycle).