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list_services

List the SDMX services this server can query, with capability notes for each, to help select a source for official statistics.

Instructions

List the SDMX services this server can query.

Any SDMX-REST v2 base URL also works: pass it as the service argument to any other tool. The service must return structural metadata as SDMX-JSON 2.0.0 and data as SDMX-CSV.

Returns: The known services, with capability notes for each.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
servicesYes
next_stepYes
custom_endpoints_supportedNoEvery tool accepts a 'service' argument holding either a known name or an arbitrary SDMX-REST v2 base URL.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the tool's behavior (lists services) and explicitly describes the return format ('known services, with capability notes'). It does not mention side effects or permissions, but listing is inherently non-destructive and the return description adds meaningful context, warranting a 4.

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?

The description is extremely concise—two sentences plus a 'Returns:' line—with the core purpose front-loaded. Every sentence adds value: it explains the tool's purpose, notes the service URL flexibility for other tools, and outlines the return. No waste or 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 the tool's simplicity (0 params, list operation) and the presence of an output schema, the description covers the essentials: what the tool does and what it returns. It could be more explicit about the possible content of 'capability notes' or how services are discovered, but it is adequate for the agent to use correctly.

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

Parameters4/5

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

The tool has zero parameters and schema coverage is 100% (empty schema). The baseline for 0 params is 4. The description adds context about passing service arguments to other tools, which is helpful for the broader workflow even though it does not directly describe this tool's parameters (none exist).

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 opens with 'List the SDMX services this server can query', clearly stating the verb, resource, and scope. It distinguishes itself from siblings like search_dataflows, inspect_dataflow, and get_data, which all focus on data retrieval rather than service enumeration.

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 implies usage by noting that any SDMX-REST v2 base URL can be passed as a service argument to other tools, which directs the user to this listing tool to discover available services before querying data. However, it does not explicitly state 'use this when you need to see available services' or provide a when-not-to-use rule, leaving some inference to the agent.

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