list_plugins
Retrieve a list of all Docker plugins installed on the system.
Instructions
List installed plugins.
returns: list - A list of plugin attrs dicts
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Retrieve a list of all Docker plugins installed on the system.
List installed plugins.
returns: list - A list of plugin attrs dicts
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, indicating a safe read operation. The description adds that it returns a list of plugin attrs dicts, but does not disclose details like disabled plugin visibility or sorting. With annotations covering safety, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short, focused sentences: one for purpose, one for return type. No filler words. Front-loaded with the action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description mentions the return type ('list of plugin attrs dicts'), which is useful. No parameters to explain. Could mention if it includes disabled plugins, but the description is sufficient for a simple list tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so schema coverage is 100%. The description does not need to add parameter info. It correctly mentions the return format, adding value. Baseline 4 applies per the guidelines for 0-parameter tools.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('list') and resource ('installed plugins'). It effectively distinguishes from siblings like install_plugin, configure_plugin, enable_plugin, etc., which involve plugin management actions beyond listing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like get_plugin (for a specific plugin) or other plugin commands. Given the many sibling tools related to plugins, explicit usage context would be helpful.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/GavinLucas/docker-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server