Luxembourg MCP

get_statistics

Retrieve recent observations from STATEC LUSTAT SDMX dataflows for Luxembourg statistics. Specify a dataflow ID and optional filters to get the latest data.

Instructions

Retrieve recent observations from a STATEC LUSTAT SDMX dataflow.

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": {
      "dataflow_id": "<dataflow_id>"
    },
    "name": "get_statistics"
  }
}

Input Schema

Name	Required	Description	Default
`key`	No	SDMX dimension key or all	all
`max_rows`	No
`dataflow_id`	Yes	STATEC identifier such as DF_D7100
`last_n_observations`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.0Jul 11, 2026

TDQS

C2.6/5.0

Behavior2/5

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

With no annotations, the description should disclose behavioral traits (e.g., read-only, rate limits, what 'recent' means). It only says 'Retrieve recent observations' – insufficient detail for an agent to understand side effects or constraints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, no wasted words. However, it is too terse and sacrifices important details for brevity. Adequate conciseness but not optimal given the tool's complexity.

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?

Tool has 4 parameters and no output schema, yet description provides no information about return format, pagination, or how parameters interact. With no annotations, this is insufficient for an agent to effectively use the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 50% (only dataflow_id described). The tool description does not add meaning to the other parameters (key, max_rows, last_n_observations) beyond what the schema provides (defaults, constraints). Baseline of 3 is not met because description fails to compensate for missing schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it retrieves recent observations from a specific dataflow (STATEC LUSTAT SDMX). It distinguishes from siblings like get_dataset (likely different scope) and search_statistics (search vs retrieve). However, 'observations' is somewhat vague without further context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives such as get_dataset or search_statistics. No conditions or exclusions mentioned.

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