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irm-kmi-mcp Belgium Weather

irm-kmi-mcp Belgium Weather

by kthys
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Daily Forecast

daily_forecast

Get a daily weather forecast for any Belgian municipality or coordinates, with official IRM bulletin text included by default.

Instructions

Return a daily weather forecast for a location in Belgium.

Each day includes the official IRM text bulletin unless include_text is false.

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": "daily_forecast"
  }
}

Input Schema

NameRequiredDescriptionDefault
daysNoNumber of days to return, clamped to ``[1, 8]``.
communeNoMunicipality name, e.g. "Namur", "Bruxelles".
languageNoBulletin language: "fr", "nl", "en" or "de". Defaults to the ``IRM_LANG`` environment variable, else English.en
latitudeNoWGS84 latitude; use with ``longitude`` instead of ``commune``.
longitudeNoWGS84 longitude; use with ``latitude`` instead of ``commune``.
include_textNoSet to false to omit the (long) official bulletin text and save tokens.

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral burden. It does disclose that each day includes the official IRM text bulletin unless include_text is false, which is useful. However, it does not explain runtime behavior such as what happens when no location is provided, how commune versus coordinates are resolved, or any side effects beyond the schema.

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 filler: the first gives the core purpose, and the second adds the key conditional behavior. It is front-loaded and every sentence earns its place.

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?

The input schema fully documents parameters and the output schema covers return structure, so the description only needs to convey the high-level contract. It does that well with Belgian scope and bulletin behavior. It is slightly light on usage routing relative to siblings, but not incomplete for invoking the tool correctly.

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 documents all six parameters. The description only restates the include_text behavior already present in the schema and adds no additional parameter-level meaning.

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 states a specific verb and resource: "Return a daily weather forecast for a location in Belgium." It clearly distinguishes the tool from siblings like current_conditions, hourly_forecast, and rain_forecast by its daily horizon and Belgian scope.

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?

The intended use case is reasonably clear from the phrase "daily weather forecast," and the sibling tool names imply the contrast. However, the description never explicitly states when to prefer this tool over hourly_forecast or current_conditions, nor does it mention exclusions or fallback alternatives.

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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