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, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is clear. The description adds value by naming specific return fields (e.g., 'id, type, params'), giving the agent concrete expectations 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 with no fluff: the first delivers purpose and return fields, the second provides usage guidance. Information is front-loaded and every sentence earns its place. Ideal conciseness.
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 tool with one optional boolean parameter and no output schema, the description fully covers purpose, returned fields, and when to use it. No gaps remain for an agent to invoke it correctly.
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 the parameter 'include_inactive' clearly described in JSON Schema. The description does not elaborate on this parameter, but since the schema is self-sufficient, a baseline score of 3 is appropriate. No extra meaning is added.
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 tool lists the caller's active subscriptions, specifying the verb 'List' and resource 'subscriptions.' It distinguishes from siblings like 'subscribe,' 'unsubscribe,' and 'watches_active' by focusing on listing, not creating or managing. The mention of returned fields further clarifies scope.
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 advises using this tool to review subscriptions before adding more or to find an ID to cancel, providing actionable guidance. While it doesn't list alternatives or when not to use, the context is clear and sufficient for basic selection.
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 and ask_pipeworx_beta are currently identical, and there are six polymarket_* tools plus bet_research for the same prediction-market domain. AI visibility and company profile tools also overlap, making selection genuinely ambiguous.
All names are lowercase snake_case, which is consistent formatting, but the pattern is mixed: some are verb_noun (ask_pipeworx, generate_llms_txt, validate_claim) while many are noun-first (convective_outlook, polymarket_edges, entity_profile) or adjective-noun (recent_alerts, watches_active). It's readable but not a uniform verb_noun convention.
35 tools is above the 25-tool threshold, and more importantly the set is bloated with a general-purpose research platform when the server is named Noaa Spc. Only 4 tools actually serve the SPC domain, so the count is inappropriate for the stated purpose.
For the dominant Pipeworx domain, the surface is fairly broad (query, compare, validate, subscribe, remember), but there are notable gaps: no update for subscriptions, no generic weather beyond SPC, and no direct list of all available sources. For the SPC purpose implied by the name, only 4 of 35 tools exist, so coverage is severely skewed.