Skip to main content
Glama
Sign In
GPU Manager MCP

GPU Manager MCP

by quxlzx
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_gpu_temperature

Retrieve a GPU's current temperature in Celsius by GPU ID to monitor thermal conditions and detect overheating risks.

Instructions

GPU temperature in Celsius (edge sensor where available).

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_temperature"
  }
}

Input Schema

NameRequiredDescriptionDefault
gpu_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full disclosure burden. It does add useful behavior beyond the schema: the unit is Celsius and the sensor is the edge sensor "where available", implying a possible fallback. However, it says nothing about failure behavior for unknown gpu_id, rate limits, or whether a value may be absent for some hardware.

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

Conciseness4/5

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

One short sentence with the measurement and unit front-loaded and no wasted wording. The parenthetical caveat is the only nuance, and it earns its place.

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

Completeness3/5

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

For a simple single-parameter read tool with no output schema and no annotations, the description covers the essentials of what is returned. It leaves an agent guessing about gpu_id format and about what happens when the sensor is unavailable or the ID is invalid, which are meaningful gaps for correct invocation.

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% and the single required parameter gpu_id is entirely undocumented. The description never clarifies whether gpu_id is an index, UUID, or PCI bus ID, so it fails to compensate for the coverage gap.

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?

"GPU temperature in Celsius" gives a specific resource (GPU temperature) and a concrete measurement with its unit, which clearly separates it from siblings like get_gpu_power, get_gpu_utilization or get_gpu_memory. It stops short of explicitly naming which sibling to use instead for related metrics, so it is clear but not fully self-differentiating.

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 statement of when to reach for this tool versus the many adjacent GPU metric tools, and no prerequisites (e.g., that the GPU must be present/visible) are mentioned. An agent must infer the usage context from the name alone.

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

Deploy Server

Other Tools