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VergeOS MCP Server

by dvvincent

get_vm_drives

Retrieve disk drive information for a virtual machine in VergeOS to manage storage resources and monitor VM configurations.

Instructions

Get disk drives for a VM

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesVM ID

Implementation Reference

  • Core handler function in VergeOSAPI class that implements the logic for retrieving VM disk drives by first obtaining the machine ID from the VM details and querying the VergeOS API endpoint /api/v4/machine_drives, then filtering results.
    async getVMDrives(vmId) {
      // Get VM to find machine ID (same pattern as getVMNics)
      const vm = await this.getVM(vmId);
      const machineId = vm.machine;
      const drives = await this.request(`/api/v4/machine_drives?machine=${machineId}&fields=all`);
      // Filter to only this machine's drives (API quirk)
      return drives.filter((d) => d.machine === machineId);
    }
  • Tool schema definition including name, description, and input schema requiring a numeric VM ID.
      name: "get_vm_drives",
      description: "Get disk drives for a VM",
      inputSchema: {
        type: "object",
        properties: {
          id: {
            type: "number",
            description: "VM ID",
          },
        },
        required: ["id"],
      },
    },
  • src/index.js:560-562 (registration)
    Registration and dispatch of the get_vm_drives tool within the main tool call handler switch statement.
    case "get_vm_drives":
      result = await api.getVMDrives(args.id);
      break;
  • Alternative direct-mode handler with additional field mapping including computed size_gb.
    async function getVMDrives(vmId) {
      // Get VM to find machine ID (same pattern as getVMNics)
      const vm = await getVM(vmId);
      const machineId = vm.machine;
      const drives = await apiRequest(`/api/v4/machine_drives?machine=${machineId}&fields=all`);
      return drives.filter(d => d.machine === machineId).map(d => ({
        id: d.$key, name: d.name, size_bytes: d.disksize, size_gb: Math.round(d.disksize / 1073741824 * 10) / 10,
        interface: d.interface_type, media: d.media_type,
      }));
    }
  • Schema definition in the direct proxy implementation.
    { name: "get_vm_drives", description: "Get VM disk drives", inputSchema: { type: "object", properties: { id: { type: "number", description: "VM ID" } }, required: ["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. It states the tool retrieves data ('Get'), implying a read-only operation, but does not specify aspects like authentication requirements, rate limits, error handling, or the format of returned data. This leaves significant gaps in understanding how the tool behaves.

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 a single, straightforward sentence that directly conveys the tool's purpose without unnecessary words. It is front-loaded and efficient, making it easy to parse quickly, which is ideal for conciseness.

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?

For a tool with no annotations and no output schema, the description is insufficient. It does not explain what data is returned (e.g., drive types, sizes, statuses) or any behavioral nuances like pagination or error conditions. Given the complexity of VM management and the lack of structured data, more context is needed for effective use.

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 'id' parameter clearly documented as 'VM ID'. The description adds no additional semantic context beyond this, such as examples or constraints on valid IDs. Given the high schema coverage, the baseline score of 3 is appropriate, as the schema adequately handles parameter documentation.

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 ('Get') and resource ('disk drives for a VM'), making the purpose immediately understandable. However, it does not differentiate from sibling tools like 'get_vm' or 'get_vm_nics', which also retrieve VM-related information but focus on different aspects.

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, such as 'get_vm' for general VM details or 'list_volumes' for broader storage information. It lacks any context about prerequisites, exclusions, or specific scenarios where this tool is preferred.

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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