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 readOnlyHint=true, idempotentHint=true, destructiveHint=false, which cover safety. Description adds return field details (id, type, params, timestamps, fire_count) and usage intent, but does not contradict annotations. Minor missed opportunity to explicitly state no side effects, but annotations already convey safety.
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 efficient sentences: first states purpose and output, second gives usage guidance. No unnecessary words, front-loaded with key information.
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 param, no output schema), the description, combined with rich annotations and schema, is complete. It covers purpose, return fields, and usage. The lack of an output schema is compensated by listing fields in the description.
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 for the single optional parameter include_inactive. The tool description does not add any additional meaning beyond the schema, so baseline 3 is appropriate.
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 states 'List the caller's active subscriptions', specifying verb (list), resource (subscriptions), and scope (caller's active). It lists return fields and distinguishes from sibling tools like subscribe and unsubscribe by indicating when to use it: to review before adding more or to find an ID to cancel.
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 says 'Use this to review what you're monitoring before adding more or to find an id to cancel', providing clear context for when to use (before subscribing or to get cancellation IDs) and implying alternatives (subscribe and unsubscribe).
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 tool clusters have unclear boundaries, most notably ask_pipeworx / ask_pipeworx_beta (which currently matches ask_pipeworx exactly) / ask_pipeworx_grounded, as well as bet_research and the five polymarket_* tools which all surface betting opportunities. ai_visibility_check and scan_competitor_ai_presence overlap, and entity_profile/compare_entities/resolve_entity share inputs. Extensive descriptions help differentiate, but an agent could easily misselect between near-duplicate entry points.
Names are uniformly snake_case and mostly follow verb_noun or prefix-group patterns such as ask_pipeworx_*, polymarket_*, remember/recall/forget, and subscribe/unsubscribe. Minor deviations like entity_profile and recent_changes drop the verb, but the overall convention is predictable and readable.
34 tools is beyond the 25+ threshold and the server bundles many unrelated domains—Pipeworx data research, Polymarket analysis, memory, subscriptions, AI visibility, npm scanning, and OBIS marine data. Many tools are redundant variants (six Polymarket tools, four ask_pipeworx variants) that inflate the surface area without adding distinct capabilities.
The data-query and prediction-market domains are thoroughly covered: routing, grounded answers, deep research, claim validation, entity comparison, edge detection, fill risk, and subscriptions. However, the server's namesake OBIS surface is skeletal—only occurrence samples, taxon resolution, and aggregate statistics, with no full-record access or dataset browsing—and the broad research purpose leaves notable raw-dataset access hidden behind the meta-router.