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kthys

irm-kmi-mcp Belgium Weather

Current Conditions

current_conditions

Get observed weather conditions for any Belgian location using nearest IRM station data. Provide a commune or coordinates to receive current conditions and condition code.

Instructions

Return observed weather conditions for a location in Belgium.

Conditions come from the nearest IRM weather station. The condition label is canonical English, with the raw IRM weather code exposed in condition_code.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
communeNoMunicipality name, e.g. "Namur", "Bruxelles", "Ostende".
latitudeNoWGS84 latitude; use with ``longitude`` instead of ``commune``.
longitudeNoWGS84 longitude; use with ``latitude`` instead of ``commune``.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.1.0

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are present, so the description carries the burden. It discloses useful behavior: data comes from the nearest IRM weather station, the condition label is canonical English, and the raw IRM code is exposed in condition_code. It does not cover staleness or error behavior, but the read-only nature is evident and an output schema exists.

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 short and front-loaded with the core action. The additional sentences about the IRM station and condition_code are relevant and add value without filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the output schema and full schema parameter coverage, the description covers the essential context: location scope, data source, and result labeling. It does not address behavior when no location parameters are supplied, but all parameters are optional and schema-documented, so this is a minor gap.

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 description coverage is 100%, so the schema already explains commune, latitude, and longitude. The description adds location scope ('Belgium') and the nearest-station concept, but does not meaningfully elaborate on parameter usage beyond the schema.

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?

Description uses a specific verb ('Return') plus resource ('observed weather conditions for a location in Belgium'). The word 'observed' clearly distinguishes it from the forecast sibling tools.

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 context is clear: this tool is for observed, current conditions in Belgium, versus the forecast siblings. However, it does not explicitly name alternatives or state when not to use it, so it falls just short of full guidance.

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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