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SignalGrid MCP

SignalGrid MCP

by DanFashauer
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

signalgrid_os_info

Read-onlyIdempotent

Retrieves macOS product and build versions, kernel, hostnames, uptime, and users to check OS patch level and identify console user.

Instructions

macOS product/build version, kernel, hostnames, uptime, and current users.

Use to establish OS patch level (compare product_version against Apple's latest release) and which user is on the console.

Returns: dict with keys: product_name, product_version, build_version, kernel, computer_name, local_hostname, uptime, console_user, process_user. Individual values read "unavailable"/error text when a probe fails.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "signalgrid_os_info"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.2

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare the tool as read-only and idempotent. The description adds valuable details beyond those annotations: it returns a structured dict and that individual values read 'unavailable'/error text when a probe fails, which is important for handling failures gracefully.

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 three short paragraphs, front-loaded with the core information (what data is returned), followed by a concise use case and return/failure semantics. Every sentence adds value with no waste.

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?

For a zero-parameter read-only tool with an output schema, the description covers all necessary context: the exact output keys, failure behavior, and a primary use case. It is sufficiently complete for an agent to invoke and interpret results correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are zero parameters, so the baseline is 4. The schema is empty, and the description does not need to explain parameters. It adds no parameter-specific meaning, but with no parameters, no further clarification is needed.

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?

The description clearly states the tool provides macOS product/build version, kernel, hostnames, uptime, and current users. It lists the exact dictionary keys, making the scope unambiguous and distinguishing it from siblings like signalgrid_software_updates or signalgrid_device_identity.

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?

The description gives explicit use cases: establishing OS patch level and determining the console user. It does not mention alternatives or when not to use it, but the context is clear and specific enough for an agent to select it appropriately.

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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