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infra-mcp

infra-mcp

by esp4ce
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_service_status

Check systemd state, uptime, and recent log lines for a service on a VM. Use for quick health check before requesting full logs.

Instructions

Returns systemd state, uptime, and last 5 log lines for a service on a VM. Use for a quick health check before requesting full logs.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "vm": "<vm>",
      "service": "<service>"
    },
    "name": "get_service_status"
  }
}

Input Schema

NameRequiredDescriptionDefault
vmYesVM name as defined in infra-mcp.yaml
serviceYessystemd service name; must be in the VM's allowlist

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.1.2
    • addedInput schema / properties / service / description
      Added value: +"systemd service name; must be in the VM's allowlist"
    • addedInput schema / properties / vm / description
      Added value: +"VM name as defined in infra-mcp.yaml"
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses return data clearly and implies a read-only operation. No side effects mentioned, but for a simple status check, this is sufficient.

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?

Two sentences with no wasted words. The first sentence states the output, the second gives usage guidance. Front-loaded and efficient.

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?

Given a simple tool with 2 parameters and an output schema, the description fully covers what data is returned and when to use it, meeting all needs for this low-complexity tool.

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?

Schema coverage is 100% with descriptive parameter names and descriptions. The description does not add extra semantics beyond the schema, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it returns systemd state, uptime, and last 5 log lines for a service on a VM, distinguishing itself from siblings like get_service_logs by positioning as a quick health check.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'Use for a quick health check before requesting full logs,' providing context and implicitly contrasting with the full log tool. Could add more exclusions or prerequisites but is effective.

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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