Luxembourg MCP

get_water_levels

Retrieve the latest official water level measurements from stations across Luxembourg. Optionally filter by station name for targeted data.

Instructions

Get the latest official measured water level at Luxembourg stations.

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": "get_water_levels"
  }
}

Input Schema

Name	Required	Description	Default
`station`	No	Optional station-name filter

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.0Jul 11, 2026

TDQS

B3.4/5.0

Behavior2/5

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

No annotations are provided, so the description must carry the behavioral transparency burden. It does not mention read-only nature, response format, rate limits, or any side effects. The description is too minimal for a tool without annotations.

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?

Single sentence with no filler, front-loaded with the core action. Every word is necessary and informative.

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

Completeness2/5

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

No output schema exists, but the description does not explain what the response contains (e.g., units, timestamps). Users must guess the return structure. Given the simplicity of the tool, additional context about outputs would be valuable.

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 coverage is 100% with a clear description for the station parameter ('Optional station-name filter'). The tool description adds no extra semantic value beyond what the schema provides, meeting the baseline 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 verb 'Get', the resource 'water level', and specifies scope: 'latest official measured' at 'Luxembourg stations'. It is specific and distinguishes from sibling tools like get_air_quality or get_traffic.

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?

No explicit guidance on when to use or avoid this tool versus alternatives. However, the purpose is so clear that the context (one optional parameter) implies simple retrieval. Lacks any comparison to other data retrieval tools.

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