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hanhsienlei

au-opendata-mcp

by hanhsienlei

Search Datasets

search_datasets

Find Australian federal and South Australian government open datasets by keyword, with optional format, portal, and publisher filters.

Instructions

Search Australian government datasets by keyword.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesKeywords, e.g. "bus stops", "rainfall", "hospital waiting times".
limitNoMaximum datasets to return, capped at 50.
formatNoOptional resource format filter, e.g. "CSV".
portalNo"data.gov.au" (federal, default), "data.sa.gov.au" (South Australia), or "all" to search both.data.gov.au
organisationNoOptional publisher name to filter by, as returned by list_organizations.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden, yet it discloses nothing beyond the one-line purpose. It does not say whether results are paginated, how ranking works, whether the portal parameter changes coverage, or anything about rate limits or read-only safety.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no filler or redundancy. It is efficient, though its brevity borders on under-specification rather than disciplined conciseness.

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?

An output schema exists, so return values need not be explained, and the rich schema covers all five parameters. However, for a multi-portal search tool with zero annotations, the description omits scoping behavior (e.g. that portal defaults to federal only and 'all' broadens coverage) that would help an agent call it correctly.

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 description coverage is 100%: q, limit (cap 50), format, portal, and organisation are all documented in the schema, including the portal enumeration semantics in prose. The description adds no parameter meaning beyond that, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (search) and resource (Australian government datasets) with the query mechanism (keyword). It is clear on its own, but it does not differentiate itself from siblings like get_dataset or query_resource, which an agent must infer.

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

Usage Guidelines2/5

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

No when-to-use guidance, no prerequisites, and no mention of alternatives. The agent must infer that this is the discovery entry point versus get_dataset (single record retrieval) or query_resource (data extraction) purely from the names.

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