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zskycode
by zskycode

run_container

Run a Docker container from any image, specifying environment variables, port mappings, volumes, command, container name, and detach mode.

Instructions

Run a Docker container

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
envNoEnvironment variables (e.g. ["KEY=value"])
nameNoName for the container
imageYesDocker image to run
portsNoPort mappings (e.g. ["8080:80"])
detachNoRun container in background
commandNoCommand to run in the container
volumesNoVolume mappings (e.g. ["/host/path:/container/path"])

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.3.0

TDQS

C2.9/5.0
Behavior2/5

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

Annotations are absent, so the description carries the full burden of behavioral disclosure. 'Run a Docker container' implies creating and starting a container but does not mention image pulling behavior, container lifecycle side effects, detach semantics, or what the tool returns after running.

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, front-loaded sentence with no wasted words. However, it is so minimal that it misses opportunities to add useful behavioral or usage context without sacrificing brevity.

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

Completeness2/5

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

With no annotations and no output schema, the description should compensate by explaining return values and side effects, but it does not. An agent is left without key information about what happens after invoking run_container, such as whether a container ID is returned or whether the image is pulled automatically.

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?

The input schema fully documents all seven parameters with 100% coverage, so the baseline is 3. The description itself adds no parameter-specific meaning beyond what the schema already provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific action ('Run') on a specific resource ('a Docker container'). It is distinguishable from sibling tools like stop_container, remove_container, and exec_container by its core operation, though it does not explicitly contrast itself with any sibling.

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?

There is no guidance on when to use this tool versus alternatives such as compose_up for multi-container workflows or exec_container for running commands in an existing container. The description simply states what the tool does without any contextual usage advice.

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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