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docker-mcp-server

docker-mcp-server

by L337-org
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

service_list

Read-only

List Docker swarm services on a manager node, with optional filters by ID, name, label, or mode, and an option to show only services managed by this server.

Instructions

List swarm services.

Must run against a swarm manager. One entry per service (the desired state); service_ps lists a service's tasks, and stack_services groups services by stack.

Args: filters: Filter by attributes (id, name, label, mode) managed_only: Only return services created by this MCP server (filters on the docker-mcp-server.managed label); combines with any filters given

Returns: list: One full service document ({"ID", "Spec", ...}) per service

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": "service_list"
  }
}

Input Schema

NameRequiredDescriptionDefault
filtersNo
managed_onlyNo

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?

Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds meaningful behavioral context beyond that: the swarm manager requirement, the fact that it returns desired state only, one entry per service, and the managed_only label filtering behavior.

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 well-structured with a clear opening line, followed by Args and Returns sections. Every sentence earns its place, and the most important usage constraint is front-loaded.

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 read-only list tool with two optional params and no output schema, the description covers prerequisites, result format, and sibling distinctions. An agent has everything needed to invoke this tool 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?

Schema description coverage is 0%, so the description carries the full burden. It explains filters as 'Filter by attributes (id, name, label, mode)' and managed_only as filtering on the docker-mcp-server.managed label, including how it combines with filters. This is far more informative than the bare schema.

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 opens with a specific verb and resource: 'List swarm services.' It also explicitly differentiates itself from siblings by stating that service_ps lists a service's tasks and stack_services groups services by stack, so an agent can disambiguate without opening schemas.

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 states the key prerequisite ('Must run against a swarm manager'), and clarifies what the tool returns versus alternatives. This gives an agent clear when-to-use and when-not-to-use guidance.

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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