Microburbs Australian Property Data

LGA · Rent payments

lga_area_stats_rent_payments

Read-onlyIdempotent

What renting households actually pay: weekly rent in 14 bands from under $75 to $950 or more, the median weekly rent, and who the landlord is (agent, private owner, public or community housing), for every suburb and council area.

Coverage: About 5,400 suburbs and localities and 536 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/rent-payments.

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_rent_payments"
  }
}

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_renting_households, rent_1_74_count, rent_1_74_pct, rent_75_99_count, rent_75_99_pct, rent_100_149_count, rent_100_149_pct, rent_150_199_count, rent_150_199_pct, rent_200_224_count, rent_200_224_pct, rent_225_274_count, rent_225_274_pct, rent_275_349_count, rent_275_349_pct, rent_350_449_count, rent_350_449_pct, rent_450_549_count, rent_450_549_pct, rent_550_649_count, rent_550_649_pct, rent_650_749_count, rent_650_749_pct, rent_750_849_count, rent_750_849_pct, rent_850_949_count, rent_850_949_pct, rent_950_plus_count, rent_950_plus_pct, rent_not_stated_count, rent_not_stated_pct, landlord_real_estate_agent_count, landlord_real_estate_agent_pct, landlord_private_person_count, landlord_private_person_pct, landlord_state_housing_count, landlord_state_housing_pct, landlord_community_housing_count, landlord_community_housing_pct, landlord_other_count, landlord_other_pct, landlord_not_stated_count, landlord_not_stated_pct, median_rent_weekly. 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

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and openWorldHint=false, so the safety profile is settled. The description adds behavior annotations do not carry: coverage (~5,400 suburbs, 536 LGAs), deliberate omission of areas with sparse populations, a single 10 August 2021 snapshot, and a 5¢ per-call price.

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?

Front-loaded with what the data contains, then coverage/freshness, then price. Three compact blocks, no wasted sentences, with the price and snapshot date isolated so they are hard to miss.

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?

Good on coverage, freshness, cost and field inventory. However, it never explains what `from`/`to` do against a single 2021-08-10 snapshot — a real ambiguity for a required-lga_name, 4-param tool — and it says nothing about the response shape despite having no output schema.

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

Parameters5/5

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

Schema coverage is 100%, and the description still adds real value: it enumerates the rent bands, the landlord categories, and the median field that `fields` can select, and points to `/v1/datasets/rent-payments` for the full field list and method.

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?

States a specific resource and payload: what renting households pay — weekly rent in 14 bands from under $75 to $950+, median weekly rent, and landlord type (agent, private owner, public/community housing) — for suburbs and council areas. This distinguishes it from siblings such as lga_area_stats_mortgage_repayments (mortgage vs rent) and suburbs_area_stats_rent_payments (suburb grain vs LGA grain).

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

Usage Guidelines3/5

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

Usage is implied by the scope statement (LGA-level rent data) and by the required lga_name tied to `/v1/lga/list`; an agent can infer the geography grain. But there is no explicit when-to-use vs the suburb variant or the mortgage-repayment dataset, and no stated exclusions.

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

All Microburbs Australian Property Data tools Inspect

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