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=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, so the description does not need to restate these. Description adds that it returns specific fields and mentions the optional parameter, which is sufficient. Could note if there is pagination, but not necessary for a simple list tool.
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 concise sentences: first states what the tool does and returns, second provides usage guidance. No unnecessary words. Front-loaded with the main purpose.
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 no output schema, description adequately lists return fields. Tool is simple with no required parameters. Usage guidance and behavioral context are covered. Could mention ordering or limit, but not critical.
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?
Only one parameter (include_inactive) with 100% schema coverage. Description restates that it includes cancelled subscriptions, which matches the schema description. No additional value added beyond schema. 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 clearly states 'List the caller's active subscriptions' with specific verb and resource. It distinguishes from sibling tools like subscribe and unsubscribe by focusing on listing existing subscriptions. Lists specific return fields for clarity.
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 tells when to use the tool: 'review what you're monitoring before adding more or to find an id to cancel.' This provides clear context and implies alternatives (subscribe for adding, unsubscribe for canceling).
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 occupy the same functional space: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, and the Polymarket cluster (polymarket_edges, polymarket_arbitrage, polymarket_edge_tracker, polymarket_fill_risk, bet_research) heavily overlaps in purpose. The only clearly separated tools are the two DMV-specific ones, but they are drowned out by ambiguous data-query and prediction-market tools.
Tool names mostly follow a predictable snake_case verb_noun pattern such as list_subscriptions, resolve_entity, validate_claim, and the polymarket_* / or_dmv_* prefixes are consistent. Minor deviations like bet_research, pipeworx_feedback, and ask_pipeworx_beta break the pattern slightly, but the overall style is coherent and readable.
A server named 'Oregon DMV' exposes 33 tools, only 2 of which relate to DMV office locations and wait times. The other 31 tools form a broad general-purpose data and prediction-market platform, making the count and scope an extreme mismatch for the stated server identity.
For an Oregon DMV server, the surface is severely incomplete: there are no tools for appointments, forms, fees, licensing, registration, or services. The two DMV tools cover only office addresses and live wait times, covering a tiny slice of the domain implied by the server name.