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AusEcon MCP for ABS | RBA | APRA data

AusEcon MCP for ABS | RBA | APRA data

by AnthonyPuggs
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

List Catalogue

list_catalogue
Read-onlyIdempotent

Browse curated ABS, RBA, and APRA catalogue entries. Filter by source, category, or tag to locate relevant Australian economic datasets.

Instructions

List curated ABS, RBA, and APRA catalogue entries, optionally filtered by source, category, or tag. Unranked complement to search_datasets.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_catalogue"
  }
}

Input Schema

NameRequiredDescriptionDefault
tagNoOptional curated catalogue tag filter.
sourceNoOptional source filter. Use abs for Australian Bureau of Statistics, rba for Reserve Bank of Australia, or apra for Australian Prudential Regulation Authority.
categoryNoOptional curated catalogue or semantic concept category filter.
include_ceasedNoWhether to include ceased ABS catalogue entries.
include_discontinuedNoWhether to include discontinued RBA catalogue entries.

Output Schema

NameRequiredDescriptionDefault
resultYesCurated ABS, RBA, and APRA catalogue entries.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover read-only, idempotent, and non-destructive behavior, and the description adds useful behavioral context: the results are 'curated', limited to ABS/RBA/APRA sources, and 'unranked' compared to search. This goes beyond the structured annotations without contradicting them, though it does not detail pagination or response shape.

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 deliver the core purpose, scope, filters, and the key differentiator from a sibling tool. Every word earns its place, and the most important information is front-loaded.

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?

Given the presence of an output schema and rich annotations, the description sufficiently covers purpose, scope, filter options, and relationship to the alternative search tool. It is complete for a simple filtered-list operation, and no critical behavioral gaps remain.

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?

All five parameters are fully documented in the schema (100% coverage), so the baseline applies. The description mentions source/category/tag filters but adds no additional meaning beyond the schema; the include_ceased and include_discontinued parameters are covered entirely by schema descriptions.

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 uses a specific verb ('List') and a clear resource ('curated ABS, RBA, and APRA catalogue entries'), and it explicitly distinguishes itself from the sibling tool 'search_datasets' by calling itself an 'Unranked complement'. This makes the tool's purpose immediately clear and resolves ambiguity among related list/search tools.

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

Usage Guidelines5/5

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

The description states the supported filter dimensions ('source, category, or tag') and frames the tool as the unranked counterpart to 'search_datasets', which implies when to choose this tool versus a ranked search. This is clear usage guidance even though it does not enumerate formal exclusions.

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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