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docker-mcp-server

docker-mcp-server

by L337-org
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Python
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container_start

Start a stopped Docker container by ID or name, resuming it without recreation. For already-running containers, no action is taken.

Instructions

Start an existing stopped container.

Use this to restart a container that was previously created or stopped without removing it. To create and start a new container in one step use container_run instead. Calling on an already-running container has no effect (the daemon returns 304 and no error is raised). To stop then start a running container use container_restart.

Args: id_or_name: Container id (full or short) or name

Returns: dict: The container's full inspect payload after starting

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": {
      "id_or_name": "<id_or_name>"
    },
    "name": "container_start"
  }
}

Input Schema

NameRequiredDescriptionDefault
id_or_nameYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.0.0

TDQS

A5/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint=false, destructiveHint=false), the description discloses the important idempotency behavior: calling on a running container has no effect and the daemon returns 304 without error. It also states the return payload is the full inspect result.

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 well-structured and front-loaded: purpose first, usage alternatives second, then Args and Returns. Every sentence provides actionable information with no padding.

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 single-parameter tool with no output schema, the description covers selection, invocation, edge-case behavior, and return format. An agent has everything needed to invoke it correctly.

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

Parameters5/5

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

The input schema has 0% description coverage, but the description compensates fully by explaining id_or_name as 'Container id (full or short) or name.' This adds essential meaning the schema alone does not provide.

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?

States a specific verb and resource: 'Start an existing stopped container.' It clearly distinguishes itself from sibling tools by naming container_run and container_restart, so an agent can immediately understand its unique role.

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?

Provides explicit when-to-use guidance with alternatives: use container_run for create-and-start, use container_restart for stop-then-start, and notes the idempotent behavior on already-running containers. This fully routes the agent to the correct tool.

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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