swiss-environment-mcp

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env_wildfire_danger

Read-only

Get current wildfire danger index for Swiss regions or cantons, updated daily on a 5-level scale. Use it to assess fire risk for events, school trips, and forestry.

Instructions

Ruft den aktuellen Waldbrandgefahren-Index nach Regionen ab.

Die Waldbrandgefahr wird täglich durch das BAFU berechnet und auf einer 5-stufigen Skala (gering bis sehr gross) kommuniziert. Relevant für Schulausflüge, Events und Forstbetriebe.

<use_case>Waldbrandgefahr-Index pro Region/Kanton, z.B. für Forstbetriebe oder Event-Planung.</use_case> <important_notes>5-stufige Skala, tagesaktuell (de/fr/it/en). Ohne Kanton-Filter werden die höchsten Stufen zuerst und auf 40 Regionen begrenzt gezeigt. Datenzugriff über einen zweistufigen, HTML-getragenen Vertrag (react-props der Startseite → signierte Blob-JSON-URL).</important_notes>

Args: params (WildfireDangerInput): - language: 'de', 'fr', 'it' - canton: Kantonskürzel zum Filtern

Returns: str: Aktuelle Waldbrandgefahr nach Regionen/Kantonen.

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": {
      "params": "<params>"
    },
    "name": "env_wildfire_danger"
  }
}

Input Schema

Name	Required	Description	Default
`params`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.5.2Jul 29, 2026

TDQS

A4.6/5.0

Behavior5/5

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

The description goes well beyond the annotations (readOnlyHint, openWorldHint) by detailing the data access mechanism (two-step HTML-backed contract), daily updates, language support, the 5-level scale, and the filtering behavior. This provides rich, non-contradictory behavioral context.

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?

The description is moderately sized with clear tags (<use_case>, <important_notes>) and a direct first sentence. It is structured but could be slightly more concise without losing essential information.

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 the tool's moderate complexity (one nested input parameter, output as string, and data source details), the description provides sufficient context for an agent to use it correctly. The presence of an output schema (implied) and the detailed notes make it complete within its domain.

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?

Although the schema descriptions already cover the parameters (canton and language), the tool description adds value by explaining the default behavior when no canton is given (highest levels first, limit 40) and the broader context of the five-step scale. This compensates for the 0% schema description coverage.

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 retrieves the current forest fire danger index by region, computed daily by BAFU on a 5-level scale, and specifies its relevance for school trips, events, and forestry operations. This is a specific verb+resource with sufficient detail to distinguish it from sibling environmental 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 description provides explicit use cases (forest operations, event planning) and contextual notes (daily updates, canton filtering, default behavior when no filter is applied). However, it does not explicitly state when not to use the tool or suggest alternatives, falling short of a perfect score.

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