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Glama

get_docker_container_stats

Retrieve live CPU, memory, network I/O, and PID stats for running Docker containers. Pass comma-separated container IDs/names or 'all' to sample them in one call.

Instructions

Returns live CPU, memory, network I/O, and PID stats for running containers. Params: container_ids comma-separated or 'all' (running only). Read-only, one-shot sample. Stats only exist for running containers; unknown or stopped ids error. Use container_ids 'all' to cover every running container in one call.

Input Schema

NameRequiredDescriptionDefault
container_idsYescontainer name(s) or ID(s), comma-separated, or 'all' for all running containers

Output Schema

NameRequiredDescriptionDefault
errorsNo
containersYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose meaningful traits: read-only, a one-shot sample (not a stream), and the failure mode for unknown/stopped ids. It omits auth/permission requirements and any concurrency or rate-limit behavior, so it is strong but not exhaustive.

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?

Four short sentences, front-loaded with what is returned, then param usage and error behavior. Slight redundancy: the running-only scope is stated in sentence one and again in sentences three and four.

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

Completeness4/5

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

An output schema exists, so return values need no explanation, and the description covers scope, parameter usage, and error cases. The one gap is that it never positions itself against the many overlapping docker siblings, which is the main thing an agent could still get wrong.

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

Parameters3/5

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

Schema description coverage is 100% and there is a single parameter, so the schema already documents container_ids fully. The description restates the comma-separated/'all' semantics and adds the useful error constraint for stopped ids, but adds no syntax beyond the schema baseline.

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?

States a specific verb and resource ('Returns live CPU, memory, network I/O, and PID stats for running containers') and scopes it to running containers. It does not, however, distinguish itself from the close sibling get_docker_container_top or get_docker_container_details, so the agent must infer the boundary.

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

Usage Guidelines4/5

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

Gives clear operating context: stats only exist for running containers, unknown or stopped ids error, and 'all' covers every running container in one call. There is no explicit when-to-use-this-vs-an-alternative statement (e.g. vs get_docker_container_top), which keeps it below a 5.

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