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 declare readOnly, idempotent, non-destructive. Description adds scope (caller's subscriptions), default behavior (active only), and return fields, adding value 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, no redundant words, front-loaded with purpose and key details.
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 list tool with no output schema, description explains return fields and scope. Combined with annotations, provides complete understanding for use.
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 (description for include_inactive). Description does not add extra details beyond schema, so baseline 3.
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?
Clearly states the tool lists active subscriptions for the caller, specifies returned fields (id, type, etc.), and distinguishes from sibling tools like subscribe/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.' Provides clear context for appropriate 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.
Multiple tools appear to do nearly the same thing, notably ask_pipeworx and ask_pipeworx_beta (the description explicitly says they currently match exactly), plus ask_pipeworx_grounded and deep_research which are all variations of the same routing/query capability. The Polymarket tools and the AI-visibility tools also have overlapping boundaries, making it easy for an agent to pick the wrong one.
Most tools follow a readable snake_case verb_noun pattern like ask_pipeworx, compare_entities, resolve_entity, scan_dependency, and validate_claim. There are minor deviations such as entity_profile, bet_research, pipeworx_feedback, and recent_changes, but the naming is largely predictable and clearly grouped by prefixes like polymarket_ and pipeworx_.
With 33 tools, this server exceeds the threshold where the count becomes a burden rather than a benefit. The set covers many disparate domains—general data querying, Polymarket betting, plant taxonomy, npm auditing, AI visibility, memory, and subscriptions—so the surface feels over-scoped for a single server.
The core research/query workflow is well covered: discovery, lookup, grounded answers, deep research, entity resolution, comparison, validation, and change tracking are all present. Subscription and memory lifecycles are also complete; the main gaps are minor, such as no explicit tool for fetching a pipeworx:// citation URI directly.