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debugpy_list_containers

List Docker containers with running Python processes to attach debugpy for debugging and inspection.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The tool handler function decorated with @mcp.tool() that implements the debugpy_list_containers tool. It calls the helper function list_containers() and returns the results as a dictionary with container information.
    @mcp.tool()
    def debugpy_list_containers() -> dict[str, Any]:
        return {"ok": True, "containers": [c.model_dump() for c in list_containers()]}
  • Helper function that executes 'docker ps' command and parses the output to return a list of ContainerSummary objects containing container ID, name, image, status, and ports information.
    def list_containers() -> list[ContainerSummary]:
        proc = run([
            "docker", "ps", "--format", "{{.ID}}\t{{.Names}}\t{{.Image}}\t{{.Status}}\t{{.Ports}}"
        ], timeout=10)
        items: list[ContainerSummary] = []
        for line in proc.stdout.splitlines():
            parts = line.split("\t")
            if len(parts) != 5:
                continue
            items.append(ContainerSummary(id=parts[0], name=parts[1], image=parts[2], status=parts[3], ports=parts[4]))
        return items
  • Pydantic BaseModel schema that defines the structure of container summary data with fields: id, name, image, status, and ports (all strings).
    class ContainerSummary(BaseModel):
        id: str
        name: str
        image: str
        status: str
        ports: str

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