Skip to main content
Glama

container_top

Read-only

List processes inside a running container via the Docker daemon's host-level ps, needing no shell or ps binary in the image. Pass container ID/name and optional ps_args.

Instructions

List the processes running inside a container (the daemon runs ps on the host).

Works on any running container without executing anything in it, so it needs no shell or ps binary in the image — unlike container_exec with ps. Use container_stats for resource usage rather than process lists. Fails if the container is not running.

args: id_or_name - The container id or name ps_args - Extra ps arguments (e.g. "aux"); default is the daemon's standard ps invocation returns: dict - {"Titles": [ps column names], "Processes": [[one row of values per process]]}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ps_argsNo
id_or_nameYes
Behavior5/5

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

Discloses that the daemon runs ps on the host, meaning no shell or ps binary is needed in the image—a key behavioral trait not evident from schema or annotations. Also specifies the failure condition. Annotations already indicate read-only, and the description adds valuable implementation context without contradiction.

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 well-structured and front-loaded with the core purpose, followed by usage guidance, parameters, and return format. Each sentence adds value; no filler or redundancy. The length is appropriate for the tool's complexity.

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?

Covers all necessary context: the exact operation, prerequisites, alternatives, parameter meanings, return structure, and failure modes. Despite having no output schema, the description explains the return dict format explicitly. It is entirely complete for selection and invocation.

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?

The input schema has zero parameter descriptions (coverage 0%), but the description fully compensates by explaining id_or_name as container id/name and ps_args as extra ps arguments with an example 'aux' and default behavior. This is more than sufficient for correct invocation.

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 'List the processes running inside a container' with a specific verb and resource. It differentiates from siblings by explicitly contrasting with container_exec and container_stats, making the tool's unique 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 Guidelines5/5

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

Provides explicit guidance on when to use it ('Works on any running container without executing anything in it'), when not to use it ('Use container_stats for resource usage rather than process lists'), and contrasts with alternative container_exec. Also notes a failure condition ('Fails if the container is not running').

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/L337-org/docker-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server