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 annotations, the description discloses that ownership is enforced, the row is deactivated not deleted, and historical events remain accessible through recent_alerts. This adds meaningful behavioral context consistent with the idempotent and non-destructive hints.
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, front-loaded with the action, and no wasted words. Every clause adds useful information about ownership and deactivation behavior.
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 cancellation tool with annotations indicating idempotency and non-destructiveness, the description covers the key behavioral caveats and historical-data impact. No output schema is needed for this action.
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 fully documents the single 'id' parameter as a subscription uuid returned by subscribe. The description merely says 'by id' and adds no further parameter-level meaning, so baseline 3 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 opens with 'Cancel a subscription by id,' using a specific verb and resource. It distinguishes itself from siblings like subscribe and list_subscriptions by clarifying this is the cancellation 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 context: ownership is enforced and the row is deactivated rather than deleted, with historical events still available via recent_alerts. It does not explicitly name alternatives like list_subscriptions, but the ownership and historical-event guidance make when to use this tool 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.
Many tools overlap in purpose: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all provide data retrieval with subtle differences. The Polymarket suite (arbitrage, edges, edge_tracker, fill_risk, kalshi_spread) and AI visibility tools (ai_visibility_check, scan_competitor_ai_presence) also have fuzzy boundaries. While some tools are clearly distinct, the overall set has significant ambiguity that could lead to misselection.
Tool names mix conventions: some are verb_noun (search_networks, compare_entities, remember, forget), others are noun_compound (entity_profile, polymarket_edges, ask_pipeworx), and a few are verb-only (recall, forget). The pattern is inconsistent, with no clear naming strategy across the tool surface.
With 34 tools, the server is heavily overloaded. While it serves as a general data platform, many tools are meta-level (discover_tools, suggest_questions) or peripheral (subscriptions, memory). The count feels excessive for the core purpose, and many tools could be consolidated or removed.
Despite the server name 'Peeringdb', only three tools (search_networks, search_facilities, search_exchanges) directly serve that domain. The vast majority of tools cover unrelated areas (Pipeworx data, Polymarket betting, AI visibility, memory, subscriptions). For the declared purpose of PeeringDB, the surface is severely incomplete—missing common operations like retrieving network details, viewing IX members, or managing peering policies.