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Windows Developer MCP Server

Windows Developer MCP Server

by peeyushcodes
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

docker_build

Build a Docker image from a Dockerfile, setting the image tag, build context directory, and optional Dockerfile path.

Instructions

Build a Docker image from a Dockerfile.

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_build"
  }
}

Input Schema

NameRequiredDescriptionDefault
tagNoImage name and tag (e.g. "myapp:latest").
confirmNoSet to True to confirm when required by config.
contextNoBuild context directory. Default: current directory..
dockerfileNoPath to Dockerfile if not in the context root.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
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 does not mention potential side effects (e.g., modifying local Docker image storage), failure conditions (e.g., Dockerfile not found, network access), or the fact that the 'confirm' parameter may be required. This is a significant transparency gap for a tool that performs image creation.

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 a single, concise sentence ('Build a Docker image from a Dockerfile.') with no unnecessary words. All essential information about the core purpose is front-loaded and immediately understandable.

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?

The tool has 4 optional parameters and an output schema, which covers return values. However, the description lacks usage context (when to use vs alternatives) and any mention of prerequisites or behavioral caveats, making it only minimally complete for an agent to select and invoke correctly.

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 description coverage is 100%, with each parameter (tag, confirm, context, dockerfile) having a clear description in the input schema. The tool description itself adds no additional parameter semantics beyond the schema, so the baseline of 3 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?

The description 'Build a Docker image from a Dockerfile' uses a specific verb ('build') and resource ('Docker image from a Dockerfile'), making the purpose unmistakable. It distinguishes clearly from sibling tools like docker_pull (pull existing image) and docker_run (run container), so there is no ambiguity.

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?

The description provides no guidance on when to use this tool versus alternatives such as docker_pull or docker_compose_up. There is no mention of prerequisites (e.g., Docker daemon running) or exclusions (e.g., not for pulling images). It simply states what the tool does without 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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