Microburbs Australian Property Data

LGA · Building approvals by council

lga_planning_building_approvals

Read-onlyIdempotent

New dwellings approved each month in every council area from July 2021: houses, other residential (units, townhouses, apartments) and the total, with the value of the building work approved.

Coverage: 561 council areas in every state and territory; monthly, July 2021 to August 2026. Current to 2026-08-31. Full description, field list and method: /v1/datasets/building-approvals.

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_planning_building_approvals"
  }
}

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: dwellings_houses, dwellings_other_residential, dwellings_total, value_houses_k, value_other_residential_k, value_total_k. 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 read-only, idempotent, closed-world, non-destructive behavior, so the description only needs to add context — and it does: exact data vintage (current to 2026-08-31), coverage breadth (561 council areas, all states/territories), a link to the dataset documentation for method, and a per-call price of 5¢, which is a real cost signal an agent cannot get from structured fields.

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?

What it measures is front-loaded, followed by a compact coverage line and a separate price line. Every sentence carries information an agent needs (series definitions, geography, time span, vintage, cost, doc pointer) with no filler.

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?

With no output schema, the description supplies the series names and value units implied by the `fields` list and points to a full field/method reference, which is enough for a filtered read-only query. It stops short of describing return shape (row granularity, ordering, empty-result behavior), a minor remaining gap.

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?

Schema coverage is 100%, so the baseline is 3; the description earns extra by bounding the usable `from`/`to` range (July 2021 – August 2026) even though the schema's `from` example permits '2020', which warns the caller that earlier requests will return nothing. It also names the measured series that `fields` can select.

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 verb and resource — 'New dwellings approved each month in every council area' — and enumerates what is measured (houses, other residential, total, value of work). This is clearly distinguishable from the surrounding lga_area_stats_* demographics tools without needing to inspect the schema.

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?

The coverage sentence implies the tool is for LGA-level monthly building-approval data, but there is no explicit when-to-use vs when-not guidance and no named alternative (e.g. suburbs_development_council_intelligence). Usage is inferred rather than stated.

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

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?