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Schwaizer BFS MCP Server

Schwaizer BFS MCP Server

by ishumilin
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

get_dataset_metadata

Get the full metadata structure of a BFS dataset, including all dimensions, codes, and values, to understand available filters before querying data.

Instructions

Get complete metadata structure for a BFS dataset from the PXWEB API. Returns information about all available dimensions, their codes, and possible values. Use this before querying data to understand what filters you can apply.

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_dataset_metadata"
  }
}

Input Schema

NameRequiredDescriptionDefault
numberBfsYesBFS number (FSO number) of the dataset (e.g., "px-x-1502040100_131")
languageNoLanguage for dimension and value labelsen

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It states what the tool returns but does not disclose any behavioral traits such as side effects, authorization requirements, or rate limits. For a simple read-only operation, this is adequate but not thorough.

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 concise sentences with front-loaded purpose. Every word adds value; no redundancy.

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

Completeness4/5

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

Given no output schema, the description adequately explains the return content (dimensions, codes, values) and usage context. It is sufficient for a metadata retrieval tool with only two well-documented parameters.

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 both parameters are well-described in the schema. The description adds no new semantic information beyond what the schema already provides; it only rephrases the purpose.

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 'complete metadata structure for a BFS dataset', and specifies what is returned (dimensions, codes, possible values). It distinguishes from sibling tools like get_dataset_dimensions by emphasizing completeness and pre-query usage.

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 this before querying data to understand filters, providing clear context. However, it does not mention when not to use it or compare directly to siblings like get_dataset_info.

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

Deploy Server

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