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, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds useful behavior context by detailing the exact return fields and the ability to optionally include inactive subscriptions, 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-loaded with the core purpose, then returns fields, then usage guidance. Every sentence earns its place with no redundancy or filler.
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, the description covers its output (return fields), use case (review before subscribing/unsubscribing), and safety (via annotations). No output schema is needed because the return fields are explicitly listed.
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% with a well-described boolean parameter (include_inactive). The description does not add parameter-level details, but the schema is sufficient. The baseline of 3 applies when the schema does the heavy lifting.
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 and specifies the returned fields (id, type, params, created_at, last_fired_at, fire_count). It distinguishes this from sibling subscription tools like subscribe and unsubscribe by focusing on the listing action.
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 gives clear usage context: 'Use this to review what you're monitoring before adding more or to find an id to cancel.' This implies when to use the tool relative to subscribe/unsubscribe, though it does not explicitly name 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.
Several tools have overlapping or near-identical purposes, e.g., ask_pipeworx and ask_pipeworx_beta are explicitly described as currently equivalent, and polymarket_arbitrage, polymarket_edges, and bet_research all target prediction-market opportunities. Descriptions help somewhat, but boundaries remain fuzzy for agents.
Tool names follow no consistent convention: some are verb-first (get_status_cat, remember), others are noun phrases (entity_profile, deep_research), and many use domain prefixes (ask_pipeworx, polymarket_*, pipeworx_feedback). While snake_case is maintained throughout, the structural pattern is mixed and unpredictable.
At 33 tools, the server is well beyond the typical well-scoped range (3-15). The count is inflated by multiple overlapping meta-tools and unrelated utility groups (HTTP cats, Pipeworx research, prediction markets, memory, subscriptions), making the set feel bloated rather than focused.
The server name 'httpcat' implies HTTP status-cat functionality, but only 2 of 33 tools serve that purpose, leaving the named domain largely uncovered. As a general-purpose data server, the collection still has gaps (e.g., no direct trading, no general web search) and appears to be a random assortment of features rather than a coherent product.