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?
The description discloses returned fields (id, type, params, created_at, last_fired_at, fire_count) and defaults (only active subscriptions). Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=true; the description adds value by detailing output composition and filtering behavior.
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: first states purpose and return fields, second gives usage guidance. No wasted 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?
For a simple list tool with one optional parameter, no output schema, and complete annotations, the description provides sufficient context about return fields and usage. No gaps given complexity.
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 the parameter 'include_inactive' fully described. The description uses 'cancelled' instead of 'inactive' in schema, adding slight clarification, but overall the parameter details are already in 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?
The description clearly states the tool lists the caller's active subscriptions, specifying the verb 'List' and resource 'subscriptions'. This distinguishes it from sibling tools '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?
The description advises using the tool to review monitored subscriptions before adding more or to find an id to cancel, providing explicit use cases. It implies when not to use (e.g., to avoid duplicate subscriptions) but does not explicitly name alternatives.
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.
The set mixes several overlapping families: ask_pipeworx and ask_pipeworx_beta are described as currently identical, while ask_pipeworx_grounded, deep_research, bet_research, and validate_claim all route to the same underlying data sources. Polymarket tools (arbitrage, edges, edge_tracker, fill_risk, spread) also blur together; only the four lookup_* VirusTotal functions are cleanly distinct.
Names are uniformly snake_case with a few consistent families (lookup_domain/file/ip/url, ask_pipeworx_*, polymarket_*), which helps. However, the set mixes imperative verbs (remember, forget, subscribe, validate_claim), noun phrases (entity_profile, deep_research, recent_alerts), and inconsistent prefixes, so no single naming convention holds across the server.
35 tools is too many for the apparent purpose, especially for a server named Virustotal. The bulk of the tools address unrelated Pipeworx research, memory, and prediction-market functions, so the count does not reflect the server's advertised domain.
For a VirusTotal server, only four lookup tools exist and there is no way to submit a URL/file, create a scan, retrieve analysis details, or explore relationships—core VirusTotal operations are missing. Scoped broadly, the unrelated Pipeworx tools are extensive, but they do not fill the gaps in the advertised domain. The surface is severely incomplete relative to the server name.