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?
The description adds significant behavioral detail beyond the annotations: ownership enforcement, deactivation instead of deletion, and the link to historical events via 'recent_alerts'. This complements the annotations (destructiveHint=false, idempotentHint=true) without contradicting them, giving the agent a clear picture of side effects.
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'), followed by two high-value behavioral notes. Every sentence earns its place; there is no fluff or repetition.
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 single-parameter tool with no output schema, the description covers the essential aspects: what it does, who can use it, and what happens to the data. It also references 'recent_alerts' for post-cancellation visibility, making the behavior predictable. The annotations enrich this further, so the tool is fully specified for an agent.
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 describes the 'id' parameter completely ('Subscription id (uuid) returned by subscribe'), achieving 100% coverage. The description only says 'by id', adding no new meaning. Per the rubric, high schema coverage yields a baseline of 3, and no extra parameter insight is provided.
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's function with a specific verb and resource: 'Cancel a subscription by id.' This distinguishes it from sibling tools like 'subscribe' (create) and 'list_subscriptions' (query). The action is unambiguous and directly tied to the tool name.
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 implies the usage context: use when you need to cancel a subscription, and clarifies ownership constraints ('you can only cancel your own subscriptions'). It also indicates a key consequence (deactivation, not deletion). However, it does not explicitly name alternatives or exclusions, 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.
Many tools overlap in purpose: ask_pipeworx, ask_pipeworx_grounded, and deep_research all answer questions; multiple prediction market tools (polymarket_edges, polymarket_arbitrage, polymarket_edge_tracker, polymarket_fill_risk) have subtle distinctions. An agent would struggle to choose correctly among these.
Tool names follow a consistent snake_case verb_noun pattern (e.g., list_subscriptions, generate_llms_txt). A few are noun phrases (stable_phases) but the style is uniform and predictable.
33 tools is high for a single server, especially given the mix of two unrelated domains (materials database and general data querying). Many prediction market tools could be consolidated, and the broad scope suggests over-engineering.
The materials data side covers search and retrieval adequately. The query side offers many capabilities but has redundant paths (e.g., multiple ways to ask questions) and gaps in editing or updating data. Overall coverage is mixed.