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Windows Developer MCP Server

Windows Developer MCP Server

by peeyushcodes
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

docker_compose_down

Stop and remove Docker Compose services, optionally deleting named volumes, with confirmation.

Instructions

Stop and remove Docker Compose services.

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": "docker_compose_down"
  }
}

Input Schema

NameRequiredDescriptionDefault
fileNoPath to the Compose file.docker-compose.yml
confirmNoSet to True to confirm.
volumesNoIf True, also remove named volumes.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'stop and remove' but does not disclose that confirmation is required (confirm param), that named volumes are only removed if volumes=true, or that networks are also removed by default. The lack of detail on destructive side effects makes it risky for an agent to invoke without further clarification.

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 a single concise sentence with no wasted words, clearly conveying the verb and resource. However, it is so terse that it omits important context, so it doesn't achieve the ideal balance of brevity and informativeness (a 5).

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

Completeness3/5

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

Given that the schema fully describes all parameters and an output schema exists, the description is minimally sufficient for simple invocation. However, it lacks usage guidance, does not mention the confirmation requirement, and does not clarify what exactly is removed (e.g., containers, networks, volumes). These gaps reduce completeness for safe and correct use.

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

Parameters3/5

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

Schema descriptions cover all three parameters (file, confirm, volumes) with clear meanings, so the description adds no additional parameter semantics. Baseline 3 is appropriate as the schema does the heavy lifting and the description does not contradict or augment it.

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 the action ('stop and remove') and the resource ('Docker Compose services'), distinguishing it from siblings like docker_stop (stop a container) or docker_remove_container (remove a container). The scope is specific to Compose-managed services, making the purpose unambiguous.

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

Usage Guidelines2/5

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

No guidance is provided about when to use this tool versus alternatives such as docker_stop, docker_remove_container, or docker_compose_up. The description does not mention prerequisites, common workflows, or exclusions, leaving the agent to infer usage from the name alone.

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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