List servers
gpucloud_list_serversGPU servers of the account (status, IPs, rate, paid-until date, suspension). (permission: servers:read) [Requires a free GPU Cloud account and MCP key]
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
gpucloud_list_serversGPU servers of the account (status, IPs, rate, paid-until date, suspension). (permission: servers:read) [Requires a free GPU Cloud account and MCP key]
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds what the annotations do not: the required permission scope (servers:read), the account/MCP-key prerequisite, and the set of fields returned, which is valuable behavioral context for a read tool lacking an output schema.
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 short clauses with no filler: the resource and returned fields come first, followed by the permission and account prerequisites. Every word earns its place and nothing is repeated from the structured fields.
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 no-argument, read-only list tool with no output schema, the description compensates by enumerating the returned fields and stating auth/permission requirements. It omits pagination behavior and result ordering, which are the only remaining gaps for an agent calling this tool.
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?
This tool takes zero parameters, so per the baseline there is no parameter semantics to document and the description cannot add value here. It does not misdescribe any input, so the neutral baseline of 4 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 states a specific resource ('GPU servers of the account') and enumerates the fields returned (status, IPs, rate, paid-until date, suspension), so an agent knows this enumerates servers rather than fetching one. It does not explicitly name the verb 'list' or distinguish itself from the sibling gpucloud_get_server, but the plural resource makes the distinction inferable.
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 prerequisites ('Requires a free GPU Cloud account and MCP key') and a permission scope, which is genuinely useful context, but it never says when to use this versus gpucloud_get_server or the metrics/usage siblings, nor any exclusion. Usage is only implied by the plural resource.
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.