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 and destructiveHint=false, so the safety profile is clear. The description adds that it returns specific fields and lists only active subscriptions by default, which is useful but not critical 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?
The description is two concise sentences. The first delivers purpose and return fields, the second gives usage guidance. No unnecessary words.
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 read-only tool with one optional parameter and no output schema, the description covers what it does, what it returns, and when to use it. The annotations cover safety. No gaps.
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?
The schema already provides a description for the single optional parameter (include_inactive). The tool description says 'active subscriptions,' implying the default behavior, but adds no new semantic meaning beyond the schema. With 100% schema coverage, baseline is 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?
The description clearly states the action (list), resource (subscriptions), and scope (caller's active). It lists the specific return fields, making the purpose unambiguous. It distinguishes from sibling tools like subscribe or unsubscribe, which involve creating or deleting subscriptions.
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 explicitly tells when to use this tool: 'review what you're monitoring before adding more' and 'find an id to cancel.' While it does not contrast with all alternatives, the guidance is direct 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.
Multiple near-duplicate clusters exist: ask_pipeworx, ask_pipeworx_beta (explicitly identical to the stable router right now), and ask_pipeworx_grounded all route through the same 5,767-tool catalog, and six polymarket_* tools overlap heavily in surfacing bet/edge opportunities. The blocklist tools (list, recent, aggressive) are only weakly distinguished by time window and confidence, requiring careful reading to select correctly.
Naming mixes several incompatible conventions: bare adjectives/nouns for blocklist tools (aggressive, list, recent), brand-prefixed compounds (polymarket_arbitrage, pipeworx_feedback), verb_noun pairs (check_ip, resolve_entity), and noun phrases (entity_profile, bet_research). The server name 'Feodotracker' appears nowhere in the tool names, and the blocklist cluster uses a completely different style from the data cluster.
At 35 tools, the count exceeds the 25-tool threshold for 'too many', but the deeper issue is that roughly 31 tools serve a general data-lookup/prediction-market platform while only 4 serve the server's stated Feodotracker blocklist purpose. The count reflects two unrelated products merged into one MCP server rather than a well-scoped tool surface.
For the named Feodotracker domain, the surface is thin: list/check/recent cover basic blocklist access but miss historical lookups, per-entry threat intel, or export formats that a botnet tracker would need. For the data-lookup domain the 31-tool suite is impressively complete, but the two domains don't form a coherent whole—each leaves the other's lifecycle half-served.