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hanhsienlei

au-opendata-mcp

by hanhsienlei

List Portals

list_portals

Discover which Australian open data portals are available for querying, including dataset counts, to identify supported data sources.

Instructions

List the Australian open data portals this server can query, with dataset counts.

Call this when the user asks what data sources are available.

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the burden. It does disclose the behavioral shape of the response (a fixed enumeration including dataset counts) and 'list' implies a safe read, but it says nothing about cost of the call, whether counts are cached/live, or any permission requirements.

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 sentences, zero filler. What it returns is front-loaded and the usage trigger follows; no sentence could be removed without losing information.

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?

An output schema exists, so return-value documentation is not the description's job, and the description still conveys the essential content (portals plus dataset counts). For a no-arg read-only enumeration, nothing an agent needs to invoke it correctly is missing.

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 takes zero parameters, so there is nothing for the description to disambiguate; the empty schema is self-explanatory and the description correctly adds no parameter claims. Baseline 4 applies for a parameterless tool.

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 and resource ('List the Australian open data portals this server can query') plus the payload detail ('with dataset counts'). It implicitly separates itself from list_organizations by scoping to portals/data sources, but never names a sibling to make the distinction explicit.

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?

Gives a clear trigger condition: 'Call this when the user asks what data sources are available.' That is actionable context, but there are no exclusions or named alternatives (e.g. use list_organizations for publishers, search_datasets for keyword lookup).

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