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?
Adds significant behavioral context beyond annotations: ownership enforced, deactivation vs deletion, and historical event availability via recent_alerts. Aligns with annotations (non-destructive, idempotent).
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, all information is relevant and front-loaded. No fluff.
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?
Tool is simple (1 param, no output schema). Description fully covers purpose, side effects, ownership, and references sibling tool for historical data.
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%; the description mentions 'by id' but adds no extra meaning beyond the schema's parameter description. Baseline score applies.
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 action (cancel), the resource (subscription), and the identifier (by id). It distinguishes from sibling tools like 'subscribe' and 'list_subscriptions'.
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 states ownership enforcement (only your own subscriptions) and outcome (deactivation, not deletion). Does not mention when to avoid using or alternatives, but context is clear.
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 purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are nearly identical (beta is currently exactly the same), and scan_competitor_ai_presence is a multi-entity wrapper around ai_visibility_check. The detailed descriptions help, but an agent could easily pick the wrong variant when a simple lookup is needed.
Tool names mix verb-first patterns (ask_pipeworx, resolve_entity, scan_dependency, validate_claim) with noun-first patterns (denver_layers, entity_profile, recent_changes, pipeworx_trending, polymarket_edges). There are clear families (ask_pipeworx_*, denver_*, polymarket_*, pipeworx_*) but no single consistent verb_noun convention across the set.
34 tools is a large surface for one server, exceeding the 25-tool threshold where coherence starts to degrade. Many tools are meta-routers or near-duplicates (ask_pipeworx family), and the mix of general data access, Denver-specific queries, prediction-market analysis, memory, and subscriptions feels sprawling rather than tightly scoped.
The tool surface covers the apparent domain well: universal data lookup, grounded evidence, deep research, entity resolution, company profiles, comparisons, claim validation, AI visibility, dependency scanning, prediction-market analysis, subscriptions, and memory. Minor gaps exist (e.g., no direct update tool for subscriptions, no way to inspect the full 5,798-tool catalog locally without routing through ask_pipeworx), but agents can accomplish most workflows without dead ends.