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docker-mcp-server

docker-mcp-server

by L337-org
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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stack_list

Read-only

List all stacks deployed to a Docker swarm, returning each stack's name, service count, and orchestrator. Use it to review active swarm deployments.

Instructions

List the stacks deployed to the swarm, parsed from --format '{{json .}}'.

Requires the target daemon to be a swarm manager. compose_list is the non-swarm equivalent; drill into one stack with stack_services. Raises RemoteFailureError if the CLI call fails.

Returns: list: One dict per stack (name, services count, orchestrator)

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": "stack_list"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.0.0

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already mark it read-only and non-destructive, but the description adds valuable behavior beyond that: it parses `--format '{{json .}}'`, raises RemoteFailureError on CLI failure, and documents the return structure. This meaningfully supplements the structured metadata.

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?

Every sentence earns its place: purpose, prerequisite, alternatives, error behavior, and return format are all covered in a compact, well-organized description. No redundant or filler content.

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 there are no parametersyb and no output schema, the description covers everything needed to call the tool correctly: prerequisites, error behavior, return shape, and relationship to sibling tools. Nothing important 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 parameterslied, so there are no parameter semantics to clarify. The empty input schema is fully complete, and the description has nothing to add; the baseline of 4 for zero-parameter tools is appropriate.

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 the exact action ('List the stacks deployed to the swarm'), specifies the parsed format, and distinguishes itself from compose_list and stack_services. An agent can immediately understand what this tool does and how it differs from similar siblings.

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?

Explicitly says it requires the daemon to be a swarm manager, names compose_list as the non-swarm equivalent, and points to stack_services for drilling into one stack. This gives 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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