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GPU Manager MCP

GPU Manager MCP

by quxlzx
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_gpu_power

Retrieves the current package power draw in watts for a specified GPU, enabling power consumption monitoring and management.

Instructions

GPU package power draw in watts.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "gpu_id": "<gpu_id>"
    },
    "name": "get_gpu_power"
  }
}

Input Schema

NameRequiredDescriptionDefault
gpu_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.6/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are supplied, so the description carries the full burden. It discloses nothing about whether the value is an instantaneous snapshot or an average, the sampling window, or what happens for an invalid or idle GPU; 'package power draw' versus board power is the only real signal added.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single short sentence with the key noun and units front-loaded, so nothing is wasted — but the brevity comes at the cost of nearly all operational detail rather than from efficient editing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no annotations, no output schema, and an undocumented required parameter, the definition leaves an agent unable to determine identifier format, snapshot semantics, or failure behavior. A metric getter of this shape needs at least a sentence on those points.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% for the single required parameter gpu_id, and the description never mentions it. It does not say where the identifier comes from (list_gpus) or whether it accepts a name, index, or UUID.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific resource and metric — GPU package power draw — with units (watts), which lets an agent distinguish it from get_gpu_utilization, get_gpu_temperature and get_gpu_clocks without opening the schema. It stops short of naming any sibling or noting its per-GPU granularity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to call this instead of get_all_gpu_metrics, get_gpu_health or get_gpu_history, and no indication that it requires a specific gpu_id from list_gpus. The agent must infer the entire selection context from the tool name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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