Microburbs Australian Property Data

LGA · Mortgage repayments

lga_area_stats_mortgage_repayments

Read-onlyIdempotent

What home-owners with a mortgage pay each month: repayments in 11 bands from under $300 to $4,000 or more, and the median monthly repayment, for every suburb and council area.

Coverage: About 7,200 suburbs and localities and 498 council areas across Australia, in all states and territories (areas with too few people or homes for reliable figures are left out); one snapshot at 10 August 2021. Current to 2021-08-10. Full description, field list and method: /v1/datasets/mortgage-repayments.

Price: 5¢ per call.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "lga_name": "<lga_name>"
    },
    "name": "lga_area_stats_mortgage_repayments"
  }
}

Input Schema

Name	Required	Description
`to`	No	Last period to include, same formats as `from`.
`from`	No	First period to include: 2020, 2020-Q3, 2020-07 or 2020-07-01.
`fields`	No	Comma-separated subset of: total_mortgaged_households, mortgage_0_299_count, mortgage_0_299_pct, mortgage_300_449_count, mortgage_300_449_pct, mortgage_450_599_count, mortgage_450_599_pct, mortgage_600_799_count, mortgage_600_799_pct, mortgage_800_999_count, mortgage_800_999_pct, mortgage_1000_1399_count, mortgage_1000_1399_pct, mortgage_1400_1799_count, mortgage_1400_1799_pct, mortgage_1800_2399_count, mortgage_1800_2399_pct, mortgage_2400_2999_count, mortgage_2400_2999_pct, mortgage_3000_3999_count, mortgage_3000_3999_pct, mortgage_4000_plus_count, mortgage_4000_plus_pct, mortgage_not_stated_count, mortgage_not_stated_pct, median_mortgage_monthly. Omit for all.
`lga_name`	Yes	Council (LGA) name exactly as /v1/lga/list returns it, e.g. `Lake Macquarie`.

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 13, 2026

TDQS

B3.2/5.0

Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds genuinely non-schema information — the 2021-08-10 snapshot, exclusion of areas with too few people/homes, and a 5¢ per-call price — but says nothing about behavior on an unrecognised lga_name or the 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.

Conciseness4/5

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

Purpose is front-loaded in the first sentence, with coverage, currency and price following in short labelled lines. The suburb-and-locality claim is the only phrasing that costs more than it earns by implying scope the tool doesn't have.

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?

For a read-only, single-required-parameter dataset query with full schema coverage and no output schema, the definition supplies what an agent needs beyond the schema: time snapshot, geographic exclusions, cost, and a documentation pointer. The missing piece is clarity that only LGA names are valid inputs and where to get them, which the schema covers only partially via the /v1/lga/list reference.

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%, so parameters, formats and the full field list are already documented in the schema; baseline 3 applies. The description adds only that there are 11 bands plus a median, and points to a docs path for the field list rather than expanding on from/to/fields semantics.

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 concrete resource and measure set: mortgage repayments in 11 bands from under $300 to $4,000+ plus median monthly repayment. The one wrinkle is that it claims figures 'for every suburb and council area' while this tool is LGA-only and requires lga_name, so the scope statement blurs it against the suburbs_ sibling.

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 explicit when-to-use or when-not-to-use guidance, and no routing to the sibling suburbs_area_stats_mortgage_repayments for suburb-level queries despite the description advertising suburb coverage. Coverage and snapshot details are dataset facts, not usage instructions.

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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