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 safety profile (readOnly, idempotent, non-destructive). Description adds return field details and usage context without contradicting 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, no waste. Every sentence adds value: one for output details, one for usage guidance.
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?
Complete for a simple read-only tool with one optional param and rich annotations. No output schema needed, description covers return and usage.
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 covers the single parameter fully (100%). Description does not add extra semantic details beyond the schema, so baseline score 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?
Description clearly states 'List the caller's active subscriptions' with specific verb and resource. Returns explicit fields, distinguishing from siblings 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?
Explicitly advises when to use: 'review what you're monitoring before adding more or to find an id to cancel.' No alternative tools mentioned but context is clear.
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.
Most tools have clearly distinct purposes with detailed descriptions. However, 'ask_pipeworx' and 'ask_pipeworx_grounded' are very similar, and 'polymarket_arbitrage' and 'polymarket_edges' overlap in scope, which could cause confusion for an agent.
Tool names mostly use snake_case but mix verb-first (e.g., 'compare_entities', 'resolve_entity') and noun-first (e.g., 'air_quality', 'entity_profile') patterns. Some names are single words ('forecast', 'geocode'), showing overall inconsistency.
With 30 tools, the server covers many domains (weather, company info, betting, memory, subscriptions). While each tool serves a purpose, the count is on the higher side and could be streamlined, but it's not excessive given the diverse functionality.
The tool set provides comprehensive coverage for its domains: weather (current, forecast, air quality), company research (profile, compare, recent changes, validation), betting (research, arbitrage, edges), memory (CRUD), and subscriptions (CRUD). Minor gaps include no tool for editing subscriptions or deleting weather data, but these are outside the intended scope.