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 provide strong safety signals (readOnlyHint=true, destructiveHint=false, idempotentHint=true), so the bar for additional transparency is lower. The description adds valuable context: it scopes results to the caller, notes active-only by default, and lists the exact return fields. This enriches behavioral understanding without contradicting 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, each earning its place: the first states the operation and output fields, the second provides usage guidance. No filler, no redundancy, front-loaded with the core action.
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?
The description fully covers what the tool does, what it returns, and when to use it. The output fields are enumerated, making up for the lack of an output schema. Annotations handle safety, and sibling tools (subscribe/unsubscribe) supply surrounding context. Nothing essential is missing.
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 fully documents the lone parameter (include_inactive) with description and default. The main description's mention of 'active subscriptions' aligns with the parameter but adds no extra semantic depth. With 100% schema coverage, a baseline of 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 identifies the operation: 'List the caller's active subscriptions' – a specific verb and resource. It enumerates the returned fields and distinguishes itself from sibling tools like subscribe/unsubscribe by focusing on the review/cancel use case.
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 states when to use the tool: 'Use this to review what you're monitoring before adding more or to find an id to cancel.' This directly guides the agent to use it before adding subscriptions (subscribe) or when needing to cancel (unsubscribe), referencing the sibling tools without naming them.
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 tools overlap heavily: ask_pipeworx and ask_pipeworx_beta are documented as currently identical, ask_pipeworx_grounded/deep_research route the same class of questions, and the six polymarket_* tools plus bet_research form a confusing cluster. Some clusters (Figshare fetch/search, memory, subscriptions) are distinct, but overall boundaries are frequently unclear.
Names are uniformly lowercase snake_case and mostly follow a predictable verb_noun pattern (ask_pipeworx, list_subscriptions, resolve_entity, scan_dependency). The main inconsistency is the mix of bare-noun Figshare resource names (article, articles, collection, collections) with verb-phrase tool names.
38 tools is well above the comfortable scope for a coherent server, especially one named Figshare. Most of the surface is unrelated to Figshare, bundling Pipeworx research, Polymarket analysis, memory, subscriptions, AI visibility, and npm checks into a single connection.
The Figshare read-side is reasonably covered (search, article metadata, files, collections, categories, licenses), but there are no create/update/delete or account/upload operations. The broader advertised surface is a grab bag with no clear domain boundary, and several subdomains are shallow while prediction markets are over-represented.