Skip to main content
Glama
Sign In
docker-mcp-server

docker-mcp-server

by L337-org
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

system_version

Read-only

Retrieve Docker server version details to check feature availability. Returns engine version, API level, and component versions.

Instructions

Return Docker server version information.

Engine version, API level, and per-component versions - the first thing to check for feature availability. system_info reports runtime state (counts, drivers, swarm role) instead.

Returns: dict: {"Version", "ApiVersion", "MinAPIVersion", "Os", "Arch", "Components", ...}

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "system_version"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.0.0

TDQS

A4.7/5.0
Behavior4/5

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 meaningful behavioral context by documenting the return type and key fields, and by framing the tool's role relative to system state inspection. It does not contradict the annotations.

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

Conciseness5/5

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

The description is compact and front-loaded with the primary action, followed by a brief usage context and a clearly formatted return summary. Every sentence earns its place.

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

Completeness5/5

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

For a zero-parameter read-only tool with no output schema, the description fully covers what the agent needs: what it returns, how it differs from `system_info`, and an indication of when to invoke it. Nothing critical is missing.

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

Parameters4/5

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

The tool has zero parameters)Skip? The description correctly avoids adding parameter details where none existما.

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

Purpose5/5

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

The description states a specific verb and resource ('Return Docker server version information') and immediately distinguishes itself from the closely related sibling `system_info`. Listing explicit return fields removes ambiguity about what the tool provides.

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

Usage Guidelines5/5

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

It explicitly states when to use this tool ('first thing to check for feature availability') and names the alternative (`system_info`) with what that alternative reports instead. This gives clear routing guidance with no need for the agent to infer.

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