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Toowiredd

ChatGPT MCP Server

container_stop

Stop a running Docker container by specifying its ID or name to manage container lifecycle and resource usage.

Instructions

Stop a running container

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
containerYesContainer ID or name

Implementation Reference

  • MCP server handler for the 'container_stop' tool. Extracts the 'container' argument from the request and delegates to DockerService.stopContainer, returning the result as text content.
    case 'container_stop': {
      const { container } = request.params.arguments as { container: string };
      const output = await this.dockerService.stopContainer(container);
      return {
        content: [{ type: 'text', text: `Container stopped: ${output}` }],
      };
    }
  • Input schema definition for the 'container_stop' tool, specifying a required 'container' string parameter.
    inputSchema: {
      type: 'object',
      properties: {
        container: {
          type: 'string',
          description: 'Container ID or name',
        },
      },
      required: ['container'],
    },
  • Registration of the 'container_stop' tool in the server's listTools response, including name, description, and input schema.
    {
      name: 'container_stop',
      description: 'Stop a running container',
      inputSchema: {
        type: 'object',
        properties: {
          container: {
            type: 'string',
            description: 'Container ID or name',
          },
        },
        required: ['container'],
      },
    },
  • Core implementation of stopping a Docker container by executing the 'docker stop' CLI command.
    async stopContainer(id: string): Promise<string> {
      return this.executeCommand(`stop ${id}`);
    }
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. While 'Stop a running container' implies a state change operation, it doesn't specify whether this is reversible, what permissions are required, whether it's destructive to data, or what happens to processes inside the container. For a mutation tool with zero annotation coverage, this represents a significant gap in behavioral information.

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 extremely concise at just four words, front-loading the essential information with zero wasted language. Every word earns its place, making it easy for an AI agent to parse quickly.

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?

Given that this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'stop' means operationally, what the expected outcome is, whether there are side effects, or how this differs from related operations like 'remove'. For a tool that changes system state, more contextual information would be helpful.

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 has 100% description coverage, with the single parameter 'container' documented as 'Container ID or name'. The description adds no additional parameter information beyond what the schema provides. According to the scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description.

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 the action ('Stop') and target ('a running container'), providing a specific verb+resource combination. However, it doesn't differentiate this tool from its siblings like 'container_remove' or 'container_start', which would require more specific language about what 'stop' means in this context versus those alternatives.

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. With siblings like 'container_start', 'container_remove', and 'container_exec', there's no indication of when stopping is appropriate versus starting, removing, or executing commands in a container. The description lacks any context about prerequisites or timing considerations.

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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