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?
Discloses important behavioral traits beyond annotations: ownership enforcement, row deactivation (not deletion), and that historical events remain available via recent_alerts. Annotations already indicate non-destructive and non-read-only, and the description adds context about what 'destructive' means here.
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?
Two sentences with no wasted words. First sentence states action and constraint, second explains behavior. Front-loads the core 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?
Covers all critical aspects: action, required parameter, ownership restriction, side effects (deactivation not deletion), and linkage to sibling tool for historical data. No gaps given the tool's 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 only parameter id is fully described in the schema. The description adds value by stating it is 'returned by subscribe', linking the parameter to its source, which aids agent understanding.
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?
Clearly states the action (cancel a subscription), the resource (by id), and distinguishes from siblings like subscribe and list_subscriptions. Mentions ownership enforcement and retention of historical events, which further clarifies its role.
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?
Explicitly says when to use (cancel own subscription) and who can use it (only owner). Implicitly tells when not to use (cannot cancel others' subscriptions). References sibling recent_alerts for historical events, but no explicit exclusion of alternatives.
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 there is some overlap between ask_pipeworx, ask_pipeworx_grounded, deep_research, and similar data query tools. However, detailed descriptions help agents differentiate.
Names consistently use snake_case and a mix of verb_noun and noun_verb patterns. No camelCase is present, but some tools like 'generate_llms_txt' have embedded acronyms, which slightly reduces consistency.
33 tools is high, but the server covers a wide range of functionalities (data lookups, prediction markets, RSS feeds, memory). Some tools could be combined, but the count is within reasonable limits for a comprehensive tool server.
The tool set covers major areas like entity lookups, prediction market analysis, data retrieval, and memory management. Minor gaps exist (e.g., no RSS feed deletion tool), but overall it is quite comprehensive.