swiss-environment-mcp

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env_nabel_stations

Read-onlyIdempotent

List all 16 NABEL air-quality monitoring stations in Switzerland (code, name, canton, site type) to choose a station for current air pollution data.

Instructions

Listet alle 16 NABEL-Messstationen des nationalen Luftmessnetzes (BAFU) auf.

Das NABEL (Nationales Beobachtungsnetz für Luftfremdstoffe) misst seit 1991 kontinuierlich an 16 Standorten in der Schweiz: NO₂, O₃, PM10, PM2.5, SO₂, CO, Russ und weitere Parameter.

<use_case>Einstieg in Luftqualitätsdaten: Stationsübersicht, um danach mit env_nabel_current die Messwerte einer konkreten Station zu holen.</use_case> <important_notes>16 feste NABEL-Stationen (statisch, kein Live-Call).</important_notes>

Args: params (NabelStationsInput): - response_format: 'markdown' oder 'json'

Returns: str: Liste aller NABEL-Stationen mit Kürzel, Name, Kanton und Standorttyp. Enthält auch den Link zur BAFU-Datenabfrage.

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_nabel_stations"
  }
}

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

A4.2/5.0

Behavior4/5

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

Annotations already indicate read-only, idempotent, non-destructive. Description adds that the data is static (not a live call) and lists the measured parameters, enhancing behavioral understanding.

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?

Well-structured with use case and important notes sections, but slightly wordy. Clear and informative without being overly terse.

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?

Provides complete context: number of stations, what is measured, output structure, and how to proceed. Output schema exists, so return details are covered.

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?

The schema's parameter description already covers 'markdown' or 'json' output. The tool description does not add new semantics beyond that, resulting in a baseline score of 3.

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 lists all 16 NABEL stations, uses the verb 'auflisten', and distinguishes itself from siblings by mentioning a follow-up use case with env_nabel_current.

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?

Includes a <use_case> tag explaining it's the entry point for air quality data, and notes the stations are static. Does not explicitly state when not to use, but provides good context.

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