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 (idempotentHint, destructiveHint), the description adds crucial behavioral details: ownership enforcement (only own subscriptions) and that the row is deactivated rather than deleted, preserving historical events. This is valuable context not present in the structured 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 three sentences, front-loaded with the primary action, and every sentence adds unique value: the action, the ownership constraint, and the deactivation behavior. No wasted 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?
For a simple one-parameter tool with rich annotations and full schema coverage, the description covers all essential aspects: what it does, who can use it, what happens to the data, and where historical data remains visible. No output schema is needed for this level of simplicity.
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 already provides a complete description for the single parameter (id: 'Subscription id (uuid) returned by subscribe.'). The tool description adds no additional meaning beyond restating 'by id', so the schema carries the burden and a 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 cancels a subscription by id, with a specific verb resource pair. It distinguishes itself from siblings like subscribe and list_subscriptions by focusing on cancellation and noting the deactivation behavior.
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 context for when to use the tool: to cancel a subscription, with ownership enforcement. It does not explicitly name alternatives or exclusions, but the purpose is unambiguous and the mention of recent_alerts implicitly points to related functionality.
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.
Most tools have distinct purposes, but ask_pipeworx, ask_pipeworx_grounded, deep_research, and validate_claim have overlapping functionality in answering factual questions. The detailed descriptions help differentiate them, though some confusion may still arise.
All tool names follow a consistent snake_case convention with a verb_noun pattern (e.g., compare_entities, resolve_entity). No mixing of camelCase or other styles, making the naming predictable and uniform.
34 tools is on the higher side, but many are meta-tools (discover, feedback, subscriptions) and some are redundant (ask_pipeworx vs grounded). While the scope is broad, the count could be trimmed for tighter focus.
The server covers a wide range of domains (SEC, FDA, FRED, prediction markets, etc.) with strong read and analysis capabilities. Missing update/delete operations and direct trading, but comprehensive for data retrieval and analysis.