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. The description adds value by listing returned fields and indicating the default filter (active only), which goes 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?
The description is two sentences, front-loading purpose and output, then 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?
Despite no output schema, the description lists all return fields. For a simple read-only tool with one optional parameter, the description fully covers purpose, usage, and output.
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% (include_inactive described). The description adds semantic value by implying active subscriptions by default, which aligns with the parameter's description.
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 'List the caller's active subscriptions' and specifies the returned fields (id, type, params, etc.), which distinguishes it from siblings like 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 explicitly states when to use: 'review what you're monitoring before adding more or to find an id to cancel.' It provides clear context but does not explicitly exclude other use cases.
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 is heavily overlapped: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all serve similar factual-lookup purposes with fuzzy boundaries. The Polymarket tools and visibility tools also overlap substantially, making tool selection genuinely ambiguous despite long descriptions.
All names are lowercase snake_case, which is internally consistent, but there is no predictable verb_noun pattern: verb styles vary wildly (ask, get, list, search, recall, remember, forget, subscribe). The 'ask_pipeworx_beta' suffix also breaks naming convention.
34 tools is far too many for a server named Eurostat, and only 3 of them (get_dataset, list_datasets, search_datasets) actually serve Eurostat data. The rest is a sprawling generic Pipeworx utility surface including prediction markets, memory, subscriptions, visibility checks, and dependency scanning, which is a severe scope mismatch.
For the Eurostat-specific portion, search/list/get covers basic dataset retrieval, but the server's broader surface is a grab-bag of unrelated capabilities with no coherent domain. The true domain is unclear, and the Eurostat side lacks deeper operations like metadata lookup or bulk/time-series expansion.