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 no destructiveness. Description adds the specific return fields, which is valuable context 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, front-loaded with purpose, and no redundant information. Every sentence is meaningful.
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 and rich annotations, the description covers purpose, usage, return fields, and parameter context. No output schema, but return fields are enumerated.
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 well-described boolean parameter. The description does not elaborate further, but the schema already provides sufficient meaning.
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 it lists the caller's active subscriptions and specifies the return fields. While not explicitly differentiating from siblings, the purpose is specific and unambiguous.
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?
Provides explicit use cases: to review before adding more or to find an ID to cancel. Does not explicitly state when not to use, but the guidance is clear and actionable.
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 clear distinct purposes, but the three ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) are very similar, and there is some overlap between bet_research and polymarket_edges. Overall, the majority are well-differentiated.
Tool names follow a consistent snake_case verb_noun pattern with only minor deviations (e.g., 'chokepoints_list' vs 'chokepoint_daily_traffic'). The naming convention is predictable and clear.
At 37 tools, the surface is overly large for a focused server. Many tools are meta-tools that could have been consolidated, and the count exceeds the recommended range (25+), making it feel heavy and unwieldy.
The server covers maritime chokepoints comprehensively (list, status, daily, compare, disruptions), and the Pipeworx-based tools provide broad coverage across financial, drug, prediction market, and general query domains. There are no obvious gaps for the stated scope.