Microburbs Australian Property Data

suburbs_finder_count

How many suburbs match the filter, without paying per row. 5c.

Use this to size a result before searching: /search is capped at 25 rows per call, so total here tells you how many offset pages you need.

Price: 5¢ per call.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`filter`	No	Range filter `fieldKey:min..max` (repeatable). Valid fieldKeys: medianHousePrice, grossYield, medianRent, growthForecast4yr, growth10yrCagr, growth3yrCagr, rentGrowth3yr, soldAtLossPct, daysOnMarket, vacancyRate, unitMedianPrice, unitGrossYield, unitMedianRent, unitGrowthForecast4yr, unitGrowth10yrCagr, unitGrowth3yrCagr, unitRentGrowth3yr, unitSoldAtLossPct, unitDaysOnMarket, unitVacancyRate, stockOnMarket, monthsOfInventory, landValuePerSqm, lifestyleScore, safetyScore, hipScore, affluenceScore, renters, distanceCbdKm, publicHousingPct, overseasBornPct, welfareReliancePct, unemploymentPct, singleParentsPct, familyHouseholdsPct, privateSchoolPct, medianIncomeWeekly, communityDepthIndex, premiumRenovationIndex, homeOfficeIndex, tranquilityIndex, innovationEconomyIndex, alternativeLivingIndex, investorConcentration, negativeGearingExposure, mortgageStress. Apartment/unit metrics are the `unit`-prefixed keys (unitMedianPrice, unitGrossYield, unitMedianRent, …); the unprefixed market keys are houses. Unit data only exists where a suburb has a real unit market — coverage runs ~13-54% of suburbs depending on the field, so a unit filter implicitly excludes house-only suburbs.
`states`	No	Comma-separated states (names or abbreviations), e.g. `VIC`.
`regions`	No	Comma-separated EXACT SA4 region names — call GET /v1/suburbs/finder/regions for the list. A metro name like `Melbourne` alone will NOT match.
`property_type`	No	Legacy flag: 'unit' re-points the ten unprefixed house-market keys (medianHousePrice, grossYield, ...) at their unit column. It does NOT affect the explicit `unit`-prefixed keys, which are always units. Prefer the `unit` keys — they are visible in /fields and can be mixed with house keys in one query.	house

Output Schema

TableJSON Schema

Name	Required	Description
`data`	No	The endpoint's payload, or `null` when Microburbs has no value.
`reason`	No	Machine-readable slug naming the no-data condition (e.g. `no_avm_for_GANSW704074813`). Stable per endpoint. Omitted on success.
`message`	No	Human-readable explanation. Omitted on success.
`available`	No	`false` on no-data responses. Omitted on success — branch on `data !== null` if you want a single discriminator.

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 14, 2026

TDQS

A4.4/5.0

Behavior3/5

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

No annotations are provided, so the description carries the burden of disclosing behavior. It does disclose that the tool counts without returning rows and that it costs 5c per call, but it does not specify whether the count respects the same filters as search, what happens with unit-only filters, or any pagination/limitations on the count itself. The sibling comparison implies it is read-only and cheap, which is useful but not fully comprehensive.

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?

The description is short, front-loads the core purpose and cost, and each sentence earns its place: it states what the tool does, when to use it, and the cost. The sibling pointer and pricing are compact and directly useful.

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?

Given the tool's simplicity (count-only, no output complexity) and the rich parameter schema, the description is almost complete. It lacks a few nuances like whether the count excludes unit-only suburbs unless a unit filter is applied, but that's implied by the filter description. The output schema exists, so the return format isn't required here. Overall, it's sufficient for an agent to use correctly.

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 input schema has 100% coverage, but the description adds significant value by explaining the filter syntax clearly and, crucially, elaborating on the unit-prefixed keys and their coverage caveat (13-54% of suburbs), which is not evident from the schema alone. It also clarifies the property_type legacy semantics, which the schema's description touches but the description makes more actionable.

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?

The description clearly states it counts matching suburbs ('How many suburbs match the filter') and explicitly positions it as a lightweight alternative to /search, which is capped at 25 rows. This distinguishes it from the sibling suburbs_finder_search, making the purpose unmistakable.

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

Usage Guidelines5/5

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

It provides explicit guidance: use this to size a result before searching, and explains that the /search cap of 25 rows means the returned total tells you how many offset pages are needed. It also notes the per-call price of 5c, informing cost-conscious use.

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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