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Schwaizer BFS MCP Server

Schwaizer BFS MCP Server

by ishumilin
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

get_statistical_data

Fetch statistical data from BFS datasets with optional dimension filtering. Use dataset metadata to discover filter options.

Instructions

Retrieve statistical data from a BFS dataset using the PXWEB API. You can optionally filter by specific dimensions. Use get_dataset_metadata first to see available dimensions and values for filtering. Returns data in JSON-stat format by default.

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": {
      "numberBfs": "<numberBfs>"
    },
    "name": "get_statistical_data"
  }
}

Input Schema

NameRequiredDescriptionDefault
numberBfsYesBFS number (FSO number) of the dataset (e.g., "px-x-1502040100_131")
languageNoLanguage for results and labelsen
queryNoOptional dimension filters as key-value pairs. Keys are dimension codes, values are dimension value codes (string or array of strings). Example: {"Jahr": ["40", "41"], "Geschlecht": ["0", "1"]}
formatNoResponse format (default: json-stat)json-stat

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.9/5.0
Behavior3/5

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

No annotations provided; the description mentions default return format (json-stat) but does not cover other behavioral traits like error handling, rate limits, or required permissions.

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, no wasted words. Purpose and key usage hint are front-loaded.

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

Completeness3/5

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

Adequate for a simple retrieval tool with a required parameter, but lacks details on output structure or potential errors, which would improve completeness.

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%, and the description adds little beyond what the input schema already provides (e.g., filtering via query). Baseline score applies.

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 statistical data from a BFS dataset using the PXWEB API, with optional filtering. This distinguishes it from sibling tools which handle metadata listing or search.

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?

Explicitly advises to use get_dataset_metadata first to discover dimensions, providing clear context for when to use this tool. No contraindications given, but usage is well-scoped.

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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