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Bundesbank Dataflows

bundesbank-timeseries.reference.dataflows
Read-onlyIdempotent

Search or list Deutsche Bundesbank economic time-series dataflows — ~94 official series covering exchange rates, interest rates, money supply, prices, and balance of payments. Filter by name/id with query, or omit to list all. Use the returned dataflow_id with bundesbank-timeseries.structure and bundesbank-timeseries.data. Data: api.statistiken.bundesbank.de (Bundesbank SDMX 2.1 REST API), no auth required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoFilter dataflows by name or id substring, case-insensitive (e.g. "exchange rate", "interest", "BBEX3"). Omit to list all ~94 available dataflows.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds value beyond annotations by disclosing the data source (api.statistiken.bundesbank.de, SDMX 2.1 REST API) and that no auth is required, which is useful operational context. No rate-limit or pagination notes, but these are minor for a lightweight listing tool.

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?

Three sentences with zero waste: what the tool lists, how to filter, what to do with the result, and the data source/auth status. The most important operational detail (search/list behavior) is front-loaded, and every sentence earns its place.

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?

For a single-optional-parameter listing tool with a full output schema, the description is complete: it covers data source, authentication, scope of content, filter semantics, and downstream chaining to structure/data tools. Nothing an agent needs to invoke this correctly is missing.

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%, so the schema fully documents the query parameter, including case-insensitivity and examples. The description reinforces the filter/omit behavior but adds no new semantic detail beyond what the schema already provides, so the baseline of 3 is appropriate.

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 states a specific verb and resource ('Search or list Deutsche Bundesbank economic time-series dataflows') and enriches it with the content scope (~94 series covering exchange rates, interest rates, money supply, prices, balance of payments). It clearly differentiates from sibling tools by naming the Bundesbank source and the downstream reference.structure and data tools that consume its returned dataflow_id.

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?

The description explains when to use the tool: filter by query to find a specific dataflow, or omit to list all. It also gives downstream routing guidance ('Use the returned dataflow_id with bundesbank-timeseries.structure and bundesbank-timeseries.data'). It lacks explicit exclusion of alternatives, but the usage context is clear for a catalog-listing tool.

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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