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host_list

Read-only

List configured Docker hosts and their connection details, helping select the target daemon for subsequent operations.

Instructions

List the Docker hosts configured via DOCKER_MCP_SERVER_HOSTS.

With a single host (or the var unset) this is the one resolved daemon; with several it is the set that the host argument selects from. The default entry is the one used when host is omitted; pass a name as the host argument of daemon-backed tools (system_ping(host=...) checks one entry). The docker-mcp://hosts resource mirrors this tool.

returns: list[dict] - one per host: name; url (resolved daemon URL, null = docker-py platform default); read_only; tls (whether a per-host cert dir is configured); default (the omitted-host fallback)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds behavioral details such as resolving the daemon URL, handling of 'default', and the return format, fully enriching the annotation information.

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?

The description is informative and front-loaded with the main purpose. It includes necessary details without excessive verbosity, though it could be slightly more concise.

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?

Given no parameters, good annotations, and an explicit description of the return format (list of dicts with fields), the description is fully complete for an AI agent to understand and invoke the tool.

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 with 100% schema coverage. Per guidelines, baseline is 4. The description adds no parameter info (unnecessary) and is adequate.

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 clearly states 'List the Docker hosts configured via DOCKER_MCP_SERVER_HOSTS', specifying a verb and resource. It distinguishes from siblings by explaining how host_list relates to system_ping and the docker-mcp://hosts resource.

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?

The description explains when to use it (single vs multiple hosts), how the 'host' argument selects, and the role of the 'default' entry. It also points to an alternative (the resource mirror), providing clear context.

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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