unsubscribeCancel a subscription by id. Ownership is enforced — you can only cancel your own subscriptions. The row is deactivated (not deleted) so its historical events stay available via recent_alerts.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Subscription id (uuid) returned by subscribe. |
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?
Beyond the annotations, the description adds valuable behavioral context: ownership is enforced, the row is deactivated (not deleted), and historical events remain available via recent_alerts. This clarifies the side effects and how it interacts with other data, fully exceeding what annotations alone provide.
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 action ('Cancel a subscription by id') and immediately followed by key constraints. No wasted words; every sentence adds essential information.
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 one-parameter action, the description covers the purpose, ownership rules, and post-action effects. With annotations handling safety profile and schema covering the parameter, there are no major gaps. It mentions how historical events are preserved, which is important contextual information. No output schema exists, but the description doesn't need to explain return values for this simple cancellation operation.
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 input schema already provides 100% coverage of the single parameter 'id', including its type and that it is a subscription uuid returned by subscribe. The description does not add additional parameter meaning beyond what the schema already states, so the 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 uses a specific verb 'Cancel' with a clear resource 'subscription' and parameter 'by id'. It clearly distinguishes itself from sibling tools like subscribe and list_subscriptions by describing the action and scope. No ambiguity.
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 clearly implies when to use this tool: to cancel a subscription you own. It warns about ownership enforcement, which is a usage constraint. However, it does not explicitly state when not to use it or mention alternatives like list_subscriptions or subscribe, so it stops short of a 5.
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.