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mcp-gnu-units

info

Discovery / health-check entrypoint: report availability and version info.

Instructions

Discovery / health-check entrypoint: report availability and version info.

Returns seven keys: status ("available"), name, version (package version), python (runtime version), mcp_sdk (MCP SDK version, or "unknown"), toolsets (empty until the GNU units engine lands), and units_db — the bundled GNU units database's source, data_version, and data_updated (§2.4.6 / §5.4), read from the shipped file's own header so it can't drift. Example: {"status":"available","name":"mcp-gnu-units","version":"0.0.1", "python":"3.12.3","mcp_sdk":"2.3.0","toolsets":[], "units_db":{"source":"GNU units","data_version":"3.26","data_updated":"2026-02-25"}}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

No annotations exist, so the description carries the full behavioral burden, and it does well: it enumerates all seven return keys, explains the sentiment of each value (e.g. mcp_sdk may be 'unknown', toolsets empty until the engine lands), and notes the units_db values are read from the shipped file header so they can't drift. It stops short of any operational notes (auth, rate limits), which are largely irrelevant for a no-arg read tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the purpose in the first clause, then the return contract. The key list plus full example JSON is somewhat long, but with no output schema the example earns its place; only the redundant §-section references are arguably noise.

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?

With no input parameters and no output schema, the description must supply the return contract itself, and it does so completely — every key, its possible values, and a worked example. An agent can call this and interpret the result without guessing.

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?

The tool takes zero parameters, so per the rubric the baseline is 4. Nothing further is required or missing.

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?

States a specific role (discovery / health-check entrypoint) and the concrete payload (availability and version info), which is far more informative than the bare name 'info'. It implicitly distinguishes itself from the conversion-oriented siblings, though it never names them explicitly.

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

Usage Guidelines3/5

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

Framing it as a 'discovery / health-check entrypoint' implies it is the thing to call first to probe availability, but there is no explicit when-to-use/when-not and no mention of the alternative siblings. Usage is inferable rather than stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.