ugreen-nas-mcp

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List Docker containers

nas_docker_containers

Read-only

List Docker containers with state, image, CPU and memory use, and published ports; filter by name, status, type, or update availability.

Instructions

List containers with their state, image, CPU and memory use, and published ports (data.result[]). This is the place to read a container's CPU and memory; mem_used is a string holding bytes. The status filter takes "running" or "stopped", while the status field in the response uses a different set (CONTAINER_DETAIL_STATUS_RUNNING, _EXITED, _RESTARTING, _UPDATING), so do not feed response values back into the filter. port_mappings is only filled for running containers, so an empty list does not prove that no ports are configured. Mounts, environment variables, restart policy, network mode and health checks cannot be read through this server; point the user to the Docker app on the NAS for those.

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": "nas_docker_containers"
  }
}

Input Schema

Name	Required	Description
`name`	No	Only containers whose name contains this text.
`type`	No	Only app-center apps, plain containers, or Compose project containers.
`order`	No	Sort direction.
`status`	No	Only containers in these states.
`sort_by`	No	Sort key.
`update_state`	No	Filter by image update availability.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 13, 2026

TDQS

A4.5/5.0

Behavior5/5

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

Annotations already say this is a read-only, non-destructive, open-world operation, so the description goes further with real behavioral detail: mem_used is a string of bytes, port_mappings is only populated for running containers so an empty list is not proof of no ports, and the filter vocabulary differs from the response vocabulary. Those are exactly the pitfalls that would otherwise cause a wrong answer.

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 tool's purpose and payload are front-loaded in the first sentence, with caveats following in a logical order. Every sentence carries information about behavior or limitations, though the final sentence on unavailable fields is a longer list than strictly necessary for the tool's own operation.

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?

With no output schema, the description still indicates the result location (data.result[]) and the shapes of key fields, and covers the filter/response vocabulary mismatch and the conditional port data. For a read-only list tool with six fully documented optional parameters, nothing an agent needs in order to interpret the result correctly appears to be 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?

Schema coverage is 100%, so the baseline is 3, but the description adds meaning the schema cannot express: the status filter accepts only 'running' or 'stopped', while the response status field uses the CONTAINER_DETAIL_STATUS_* set, and it warns not to feed response values back into the filter. This clarifies a real semantic mismatch between input and output rather than repeating enum values.

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 opens with a specific verb and resource (list containers) and enumerates exactly what is returned: state, image, CPU and memory use, and published ports. It also claims a niche ('the place to read a container's CPU and memory'), which signals it is distinct from other docker tools, but it never names the sibling it differs from.

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?

It states when to use the tool ('the place to read a container's CPU and memory') and explicitly rules out capabilities that require going elsewhere: mounts, environment variables, restart policy, network mode and health checks. That negative guidance tells the agent directly when not to use the tool and where to point the user instead.

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