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 indicate readOnlyHint, idempotentHint, and non-destructive behavior. The description adds value by specifying the returned fields and the optional 'include_inactive' parameter's effect. It does not contradict 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 long with no redundant words. The first sentence lists purpose and outputs, the second provides usage guidance. Every sentence serves a purpose.
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?
Given the simplicity of the tool (no output schema, one optional parameter), the description is largely complete. It states the scope ('caller's active'), lists return fields, and provides usage advice. It could mention lack of pagination but is sufficient.
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 covers the single parameter completely (100% coverage). The description does not add additional meaning to the parameter beyond its schema definition, but it implies the parameter's effect through context. Baseline score 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 states the tool lists the caller's active subscriptions, specifying the verb 'list' and the resource 'subscriptions'. It also enumerates the return fields, making the purpose explicit. This distinguishes it from sibling tools 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 advises to use the tool 'to review what you're monitoring before adding more or to find an id to cancel'. This provides clear usage context but does not explicitly mention when not to use it or contrast with other tools like 'subscribe'.
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 significantly: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded serve nearly identical purposes, and deep_research further duplicates. Polymarket tools (bet_research, polymarket_arbitrage, polymarket_edges, etc.) also have overlapping scopes, making it hard for an agent to select the correct one without deep inspection.
Tool names use a mix of patterns: some are descriptive phrases (ai_visibility_check, generate_llms_txt), others are domain-prefixed (nz_tender_*, polymarket_*) but lack a uniform verb_noun structure. The ask_pipeworx series diverges from the rest, and verb choices are inconsistent (compare_entities vs scan_competitor_ai_presence).
With 34 tools, the surface is large and feels bloated. The server covers multiple distinct domains (NZ tenders, Polymarket, memory, subscriptions) that could be separate servers. Many tools are variants of the same core functionality (e.g., four ask_pipeworx variants), inflating the count without clear necessity.
For a general-purpose data query server, the tool set covers a broad range of sources (SEC, FDA, FRED, etc.) and includes CRUD for memory and subscriptions. However, obvious gaps exist: no dedicated web search tool (ask_pipeworx is for structured data), and NZ coverage is limited to tenders only. Missing update/delete for some resources (e.g., no way to modify a subscription beyond unsubscribe).