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 the tool as read-only, idempotent, and non-destructive. The description adds value by detailing the returned fields and default behavior (active subscriptions only), providing context beyond annotations without contradiction.
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, directly states purpose and usage, with no redundant information. It is front-loaded and efficient.
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 tool with one optional parameter and no output schema, the description covers what it does, what it returns, and a usage scenario. It is nearly complete, though it could explicitly note that it only returns the caller's subscriptions.
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 has 100% coverage for the single parameter 'include_inactive' with a clear description. The description only implies the default behavior but adds no additional meaning beyond the schema.
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 it lists the caller's active subscriptions and specifies the returned fields. It distinguishes itself from sibling tools like 'subscribe' and 'unsubscribe' by indicating its use for reviewing existing 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 offers explicit guidance to use this tool for reviewing subscriptions before adding more or to find an ID to cancel. It implies when not to use it (not for creating or canceling) but does not explicitly mention alternatives or exclusions.
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 tool set has several overlapping families: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, the discovery tools (list_datasets, discover_tools, suggest_questions) all serve a 'what can I do here' purpose, and ai_visibility_check is wrapped by scan_competitor_ai_presence. The polymarket_* tools are well-differentiated, but the heavy overlap in the meta-tools makes selection error-prone.
Naming is a mix of conventions with no unifying pattern: family prefixes appear as ask_pipeworx_*, pipeworx_*, and polymarket_*, while unrelated tools use bare nouns (entity_profile, recent_changes), verb-first names (validate_claim, search_within), and inconsistent styles. The three actual FEMA tools (disaster_declarations, list_datasets, query_dataset) share no prefix that ties them to the server's stated name.
34 tools exceeds the 'too many' threshold, and the count is unjustified by the server's apparent scope: only 3 of 34 tools relate to OpenFEMA data, with the remaining 31 being a grab-bag of Pipeworx routing, Polymarket betting, memory, subscription, and AI-visibility utilities. The bulk is either redundant with the meta-routers or off-domain for a server named 'Openfema'.
For FEMA specifically, list_datasets + query_dataset covers generic read-only access and disaster_declarations adds a convenience wrapper, but the domain is extremely thin and lacks FEMA-specific conveniences (e.g., geographic aggregation, multi-dataset joins, incident summaries). For the broader Pipeworx universe the routing coverage is actually decent, but that makes the FEMA-named server's surface feel incoherent — an agent expecting a FEMA toolset finds most of its value in unrelated prediction-market and brand-visibility tools.