Microburbs Australian Property Data is answering right now. Last checked 1 min ago. It exposes 173 tools.
Australian property and suburb data: valuations, sales, rents, schools, risk and zoning.
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173
Tools
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Access
streamable-http
What changed 9
Every tool that appeared, vanished or quietly changed what it asks for. Recorded since 17 September 2026. No other catalogue keeps this.
22 Sep
a tool disappeared
ping_head
17 Sep
8 tool descriptions were rewritten
area_stats_fields, area_stats_regions, geocode_suburb and 5 more
Microburbs Australian Property Data does not always answer
Over the last week it answered 97.8% of our checks. We check every 15 minutes, so you hear about the next outage within the hour — not from your users.
Connect this server
Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 1 min ago.
run in your terminal
claude mcp add property-data --transport http https://api.microburbs.com.au/mcp~/Library/Application Support/Claude/claude_desktop_config.json
{
"mcpServers": {
"property-data": {
"url": "https://api.microburbs.com.au/mcp"
}
}
}~/.codex/config.toml
[mcp_servers.property-data]
url = "https://api.microburbs.com.au/mcp".cursor/mcp.json
{
"mcpServers": {
"property-data": {
"url": "https://api.microburbs.com.au/mcp"
}
}
}.vscode/mcp.json
{
"mcpServers": {
"property-data": {
"url": "https://api.microburbs.com.au/mcp"
}
}
}Available tools 173
Read directly from the server with tools/list, grouped by what they act on.
If a tool disappears, we record the date.
suburbs
suburbs_crime_breakdown
Per-crime-type rates (predicted incidents per 100,000 residents
per year) for the suburb vs national medians.
suburbs_crime_by_mesh_block
Total crime rate for every mesh block in the suburb, keyed by ABS
mesh-block code. Values are predicted incidents per 100,000 residents
per year (see the payload's `unit` / `definition` keys).
suburbs_crime_summary
Suburb and national total-crime medians (predicted incidents per
100,000 residents per year) with a vs-national verdict.
suburbs_demographics_age
Population by age bracket and gender.
suburbs_demographics_all
Age + income — bundle
suburbs_demographics_ancestry_map
The dominant ancestry (and its share) in each of the suburb's
microburbs, plus suburb-level ancestry shares. Pilot coverage.
suburbs_demographics_business
ABN industry-mix pattern (Diverse / Professional-services-heavy /
Mining-exposed / Low-commercial residential) plus the POI categories
unusually common in the suburb, with named examples.
suburbs_demographics_cohorts
How the suburb ranks inside its SA4 region and against its touching
neighbours on renter share, welfare dependency, overseas-born parents
and public housing.
suburbs_demographics_cultural_integration
Suburb cultural-integration composite (0-100) with national
percentile and tier, plus the per-microburb scores behind it.
suburbs_demographics_income
Household income breakdown by bracket.
suburbs_demographics_income_map
Median weekly household income for every microburb in the suburb,
plus the suburb median, national percentile and highest/lowest pockets.
suburbs_demographics_population_history
Total suburb population is `current_population` (ABS Census 2021),
alongside suburb census points (2011/2016/2021) and the LGA's yearly
population series with a 10-year modelled projection tail. Use this route
for questions such as "what is the total population of Clarkson?
suburbs_demographics_private_school
Share of residents attending Catholic / Independent schools —
suburb rollup plus the per-microburb shares behind it.
suburbs_demographics_single_parents
Single-parent-family share for the suburb against the pinned
national median, with the associated capital-growth impact.
suburbs_demographics_tenure
Explicit total owner-occupation rate plus owned-outright / mortgaged /
renting / public-housing shares — a suburb rollup and the per-microburb
downscaled Census shares. `owner_occupied_pct` is the requested headline;
it equals owned outright plus mortgaged and is null if either is absent.
`census_year` makes the 2021 reference period explicit.
suburbs_demographics_underclass_drag
Welfare-dependency and public-housing shares with the suburb's
underclass tier (High / Mid / Low) and the capital-growth impact
associated with that tier. Regional and neighbour ranks for the same
two metrics are served by `/demographics/cohorts`.
suburbs_demographics_unemployment
Labour-force-weighted unemployment rate for the suburb against the
pinned national median, plus the per-microburb shares behind it.
suburbs_demographics_voting
Projected first-preference shares per party, aggregated across the
suburb's microburbs (booth-derived model — not an actual vote).
suburbs_development_all
DA count + DA list — bundle
suburbs_development_applications
Recent development applications (up to 100, newest first) with category counts.
suburbs_development_building_controls
Height-of-building and floor-space-ratio control polygons with band summaries.
suburbs_development_construction_activity
Satellite-detected construction change per mesh block plus a suburb rollup.
suburbs_development_council_intelligence
Council capex / project-pipeline signals extracted from the LGA's meeting
minutes — each with stage, dollar value, location and time horizon — plus a
rollup of the total pipeline in dollars.
suburbs_development_council_rates
Average annual residential council rate for the suburb's LGA.
suburbs_development_da_count
Count of recent development applications in the suburb.
suburbs_development_da_list
Recent development applications lodged in the suburb.
suburbs_development_density
Dwellings and people per km², plus the land area and counts behind them.
suburbs_development_profile
Dwelling-mix scalars — apartment share and average lot size.
suburbs_development_supply
New dwellings (last 24 months) split units vs houses per mesh block plus a rollup.
suburbs_development_zoning_map
Zoning polygons clipped to the suburb, with per-class and parent-group area shares.
suburbs_ethnicity_all
All ethnicity — bundle
suburbs_ethnicity_ancestry
Ancestry breakdown from the ABS census.
suburbs_ethnicity_birthplace
Country-of-birth breakdown from the ABS census.
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.**
suburbs_finder_fields
Every field you can filter / sort on, with its label and unit. 0c.
Houses and units are separate keys: the `unit`-prefixed ones
(`unitMedianPrice`, `unitGrossYield`, `unitMedianRent`, …) are the
apartment market, the unprefixed market keys are houses, and both can be
filtered in the same query. Unit fields are NOT nationally populated — they
only exist where a suburb has a unit market (roughly 13-54% of suburbs
depending on the field), so a suburb with no unit market simply won't match
a unit filter.
**Free.**
suburbs_finder_regions
SA4 regions grouped by state — the values accepted by `states` /
`regions` on search. 0c.
**Free.**
suburbs_finder_search
Boolean-AND range filter over suburb metrics, single-column sort,
paginated. Every row carries its `rank` — position in the ranked result
(1 = top of the sort, out of `meta.total`). When sorting by a median or a
growth, the actual value is also shown for the first 5 and last 5 rows of
the page; for any other suburb's number, call the per-field endpoint
(market/*, forecast/*).
**Paging:** a page is capped at 25 rows. A bigger `limit` is clamped, not
rejected — so always read `meta`: `total` is the full match count,
`has_more` says whether rows remain, and `next_offset` is the `offset` to
pass for the next page. A "top 50" needs two calls, each charged.
Flat 30c.
**Price: 30¢ per call.**
suburbs_forecast_sale
1-year sale-price growth forecast (low / most-likely / high).
suburbs_hero_neighbours
Nearest neighbouring suburbs with distance in km, closest first.
suburbs_hero_price_growth_12mo
12-month sale-price growth by property type (house / unit).
suburbs_hero_summary
State, SA3/SA4, postcode, population, dwellings and centroid for the suburb.
suburbs_lifestyle_cbd
Straight-line distance to the nearest city and to the nearest capital, in km.
Both, because they answer different questions and are often nowhere near
each other: Belmont North is 14 km from Newcastle and 108 km from Sydney.
`nearest_city` is usually what a buyer means by "how far is town".
The top-level `city` / `distance_km` fields are DEPRECATED. They still
describe the CAPITAL, unchanged, so existing callers are unaffected —
read `capital_city` or `nearest_city` instead.
suburbs_lifestyle_landmarks
Nearest beach and hospital with straight-line distances (null = none within ~50 km).
suburbs_lifestyle_livability
Livability scores (0–100) per dimension, aggregated from mesh-block scores, with the SA4 benchmark.
suburbs_lifestyle_livability_map
All seven livability dimensions — affluence, lifestyle, hip,
convenience, family, safety, tranquility — scored 0-100 for every
microburb (mesh block) in the suburb, each with its human band. Averaging
a dimension across the microburbs reproduces the suburb figure at
``/lifestyle/livability``. Values only; polygons come from
``/shapes/mesh-blocks``.
suburbs_lifestyle_narrative
One plain-English sentence per livability dimension for the suburb.
suburbs_lifestyle_poi_impacts
What the absence of petrol stations, fast food and bottle shops near sold properties was worth.
suburbs_lifestyle_pois
Every named venue / amenity in the suburb as GeoJSON Point features, plus a
per-category count.
Each point carries `name`, a broad `category` (Restaurant / Cafe, Shopping,
Health, Entertainment, Sport & Fitness, Education, …) and a finer `subtype`
(e.g. `pub`, `bar`, `cafe`, `restaurant`, `gym`, `supermarket`, `school`,
`pharmacy`). This is the endpoint for "what / how many <venue type> are in
this suburb" and "name the pubs / cafes / gyms in X" — filter or count the
features on `subtype`, and read real venue names from `name`. The top-level
`categories` array gives the broad-category counts without walking the list.
Unpaged by default. Big suburbs are big — Sydney is ~3.7 MB of features — so
pass `limit`/`offset` (or narrow with `category`) when you don't need them
all. `count` and `categories` always describe the whole suburb, so paging
never hides the totals. Flat price per call regardless of page size.
suburbs_lifestyle_summary
POI category breakdown, terrain scalars, nearest train/shop and beach/hospital flags.
suburbs_list
List Australian suburbs (SALs). Always returns `{suburb, state}`
per row so SAL-name collisions across states are unambiguous.
With no filter you get the first 1000 suburbs alphabetically
(browser-renderable preview). Pass any of the filters to narrow:
state / lga / sa4 / sa3 / postcode / q (name search). Filters
combine (AND). Flat cost regardless of how many rows come back.
**Name search (`q`) is typo-tolerant.** It tries an exact match, then
substring, then a fuzzy near-miss, and returns `match`
(`exact` / `contains` / `fuzzy`) and `score` on every row so you can
see which happened.
**Always tell the user which suburb you resolved to, and its state,
before quoting numbers for it.** A fuzzy match is a suggestion, not a
confirmation — `rokeby` is one letter from Kokeby in Western Australia
and Rokeby exists in both Tasmania and Victoria. If more than one
candidate is plausible, ask rather than pick.
When `q` is combined with `state`, the state is a **preference, not a
filter**: in-state candidates rank first, but a suburb of that name in
another state is still returned rather than hidden, so a near-miss
becomes "Seaview is in Victoria, not Tasmania" instead of "no data".
Every other filter stays a strict AND.
**Free.**
suburbs_listings_for_sale
Current for-sale listings in the suburb, with address, price, beds/baths
and coordinates per listing.
`total` is the full number on the market (computed before `limit`), so a
count is accurate even when the rows are capped. Raise `limit` for more
listings; set `verbose=true` for the agent's full description text.
suburbs_market_affordability
Microburbs affordability index for the suburb's postcode area.
suburbs_market_all
The eight headline market indicators in one call: median sale price and
median rent (each with its full history), 5-year price growth, gross yield,
days on market, and transaction volume.
**This is a core set, not every market endpoint.** The `Suburb - Market`
family has 29 endpoints; this bundles 8 of them, priced sum-of-parts. The
path is `/market/all` for historical reasons — it is not "all". Supply,
vacancy, growth drivers, affordability, mortgage stress, investor
concentration, land values, repeat sales, bedroom stats and the per-mesh-block
maps are separate calls, so you only pay for what you ask for.
suburbs_market_bedroom_stats
House/unit price, sales volume, median bath/car/land, and stock mix per bedroom count.
suburbs_market_built_year
Estimated build-year profile — suburb aggregate + per-mesh-block medians.
suburbs_market_comparable_suburbs
Same-SA3 comparable-suburb candidates (canonical SAL names).
suburbs_market_days_on_market
Median days on market for current listings.
suburbs_market_days_on_market_benchmark
Median days on market across the suburb's greater region (GCCSA) — compare with /market/days-on-market.
suburbs_market_growth_drivers
Per-indicator capital-growth attribution for the suburb.
Each row pairs the suburb's own value for an indicator with the
capital-growth differential our matched studies attribute to it, in
percentage points. Covers supply & demand pressure, market signals,
environmental risks and demographic composition.
suburbs_market_investor_concentration
Rental (investor) share per mesh block, with a suburb-wide rollup.
suburbs_market_land_values
Suburb land-value medians ($/sqm, lot size, land share of price) + per-mesh-block $/sqm.
suburbs_market_median_price_map
Median house price for every microburb (mesh block) in the suburb, with
its modal street name, plus the dearest and cheapest pockets. Values only —
the matching polygons come from ``/shapes/mesh-blocks``.
suburbs_market_median_rent
Latest median weekly rent for the suburb.
suburbs_market_median_rent_series
Full median weekly-rent observation history for the suburb, including
2024 and 2025 where the suburb has coverage. Older observations are
generally month-end and recent observations can be weekly; this is not a
uniformly quarterly series. Values are advertised median AUD per week.
suburbs_market_median_sale_price
Latest median sale price for the suburb.
suburbs_market_median_sale_price_series
Full median sale-price observation history for the suburb. Well-covered
suburbs extend back 20+ years; coverage and observation frequency vary.
This is the raw historical series needed to calculate a stated 20-year
return, not a precomputed "consistent growth" score or a forecast.
suburbs_market_months_of_supply
How many months the current for-sale stock would take to clear at the
suburb's current sales rate. Under 2 months is a seller's market.
suburbs_market_mortgage_stress
Mortgage-stress score (0-100) for the suburb, with per-mesh-block breakdown.
suburbs_market_price_growth
Past compound sale-price growth over 1 / 3 / 5 / 10 years, by property
type (decimal). The 3y / 10y figures are the same ones the Suburb Finder
ranks on.
suburbs_market_price_growth_5y
5-year compound sale-price growth (decimal).
suburbs_market_recent_price_movement
The last four weekly smart-median observations — house price, unit price
and house rent — each with its week-on-week percentage change.
suburbs_market_rent_map
Median advertised weekly house rent for every microburb (mesh block) in
the suburb, with its modal street name, plus the dearest and cheapest
pockets. Values only — the matching polygons come from
``/shapes/mesh-blocks``.
suburbs_market_repeat_sales
Realised resale growth — summary + individual buy/sell pairs (max 500).
suburbs_market_stock_on_market
Properties currently listed for sale in the suburb, split house/unit,
with the suburb's rank among its peers.
suburbs_market_strata_levies
Median estimated annual strata levy for the suburb.
suburbs_market_supply_pressure
For-sale listings per 100 dwellings (90 days) — per mesh block + suburb rollup.
suburbs_market_transaction_volume
Recent sale-transaction count for the suburb.
suburbs_market_vacancy_map
Calibrated rental-vacancy rate for each mesh block in the suburb.
suburbs_market_vacancy_rate
Suburb-wide rental vacancy rate by property type, as a decimal fraction
(0.00842 = 0.84%). Use `/market/vacancy-map` for the per-mesh-block surface.
suburbs_market_vacancy_rate_series
Full rental-vacancy history by property type, decimal fractions.
suburbs_market_yield_map
Gross rental yield for every microburb (mesh block) in the suburb —
weekly rent x 52 over median price — with both inputs returned so the
number is checkable, plus the best- and worst-yielding pockets. Values
only; polygons come from ``/shapes/mesh-blocks``.
suburbs_market_yield_pct
Gross rental yield = median rent annualised / median sale price.
suburbs_market_yield_pct_series
Full gross-rental-yield history by property type, decimal fractions.
suburbs_profile
The suburb's upward ABS admin chain — LGA, SA2/3/4, GCCSA,
state, postcode. Use ``/v1/suburbs/list`` to discover canonical
SAL names (and filter by state / LGA / SA4 / postcode).
suburbs_risks_all
Bushfire + flood — bundle
suburbs_risks_bushfire
Share of the suburb AREA covered by bushfire-prone designation.
Area, not properties — and the two differ a lot. Belmont North is 45.72%
by area but 23.62% by property count, because designated land is not
evenly built on. If you want "what share of homes here are affected",
which is the figure our own reports headline, use
`GET /v1/suburbs/{suburb_name}/risks/property-hazard-counts` — it returns
a count and pct per hazard against the suburb's actual dwellings.
suburbs_risks_capital_growth_impact
Matched-study capital-growth impact (%/yr) for bushfire, flood, contamination, mine subsidence, aircraft noise and surface acid sulfate, scaled by the share of properties affected.
suburbs_risks_counts
Counts of contamination points, heritage items and erosion-prone polygons inside the suburb.
suburbs_risks_extras
Landslide / storm-tide coverage, EPA notices, landlord-insurance medians and crime benchmark, with per-microburb detail.
suburbs_risks_flood
Share of the suburb AREA covered by modelled flood overlays.
Area, not properties. For the share of DWELLINGS affected — the figure our
own reports headline — use
`GET /v1/suburbs/{suburb_name}/risks/property-hazard-counts`.
To answer **where** the flood zone is, pass `geojson=true`. The response
then includes the actual modelled flood polygons clipped to the suburb
boundary, suitable for a street map, plus truncation/simplification
metadata. Do not infer street location from `coverage_pct` alone.
suburbs_risks_heritage_share
Share of the suburb's properties inside a heritage polygon.
suburbs_risks_hv_power_lines
Whether high-voltage transmission lines cross the suburb, how many, and the highest voltage class (overhead lines only).
suburbs_risks_property_hazard_counts
Counts and shares of the suburb's properties flagged bushfire / flood / mine-subsidence / contamination / aircraft-noise / acid-sulfate.
suburbs_risks_slope
Median / 90th-percentile property gradient and share of steep (>10°) properties.
suburbs_sales_recent
Properties sold in the suburb over the last 3 years, with beds/baths/land
size, sale price and date, and coordinates.
Paginated: `total` reports how many sales are available for the suburb
(counted before `limit`/`offset`), so you can page through the full feed.
Flat price per call regardless of page size.
suburbs_sales_summary
Number of sales and median sold price in the suburb over the last 3 years.
suburbs_schools_all
All schools — bundle
suburbs_schools_catchment
Public-school catchment polygons covering the suburb.
suburbs_schools_nearby
Schools serving / near the suburb, with rank + attendance data.
suburbs_shapes_boundary
Simplified SAL boundary polygon (GeoJSON Feature) plus centroid.
suburbs_shapes_busy_roads
Busy-road line segments clipped to the suburb — the report's road-noise exposure proxy.
suburbs_shapes_easements
Registered easement geometries intersecting the suburb (GeoJSON FeatureCollection).
suburbs_shapes_hazards
Hazard polygons for one layer, clipped to the suburb boundary (empty collection = hazard not present).
suburbs_shapes_mesh_blocks
ABS 2021 mesh-block polygons covering the suburb (GeoJSON FeatureCollection, MB code per feature).
suburbs_shapes_neighbours
Neighbouring suburbs as a GeoJSON FeatureCollection — each with its boundary polygon and distance in km.
suburbs_shapes_noise_heatmap
Precomputed noise colour regions clipped to the suburb, plus cell-centre heat points.
suburbs_shapes_public_housing_sa1
SA1 polygons in the suburb with their 2021 census public-housing share (only SA1s above 0%).
suburbs_similar
Top-10 suburbs ranked closest by Microburbs' similarity model.
suburbs_street_forecasts
2/4/8-year price forecasts for every street in the suburb, anchored to the real sold median.
Unpaged by default. Large suburbs are large — Point Cook has 943 streets
(~1.4 MB) — so pass `limit`/`offset` when you don't need the lot. `total`
reports how many exist. Flat price per call regardless of page size.
properties
properties_amenities_nearby
Curated amenities (supermarkets, green spaces, restaurants/cafes)
within `radius_m` of the property, bucketed and nearest-first.
**Price: 10¢ per call.**
properties_basics_all
**Price: 23¢ per call.**
properties_basics_bath_count
Bathroom count from the latest matching listing.
**Price: 5¢ per call.**
properties_basics_bed_count
Bedroom count from the latest matching listing.
**Price: 5¢ per call.**
properties_basics_dwelling_type
Dwelling type (house, unit, townhouse, ...).
**Price: 5¢ per call.**
properties_basics_land_area_sqm
Parcel land area in square metres from the cadastral feed.
**Price: 3¢ per call.**
properties_basics_parking_count
Parking-space count from the latest matching listing.
**Price: 5¢ per call.**
properties_comparables_all
**Price: 74¢ per call.**
properties_comparables_cma_comp_set
Top comparable sales used to triangulate the subject property's value.
**Price: 60¢ per call.**
properties_comparables_cma_single_comp
Single best comparable from the CMA set (highest dist_score).
**Price: 10¢ per call.**
properties_comparables_recent_sales_nearby
Recent comparable sales in a small radius around the subject parcel.
**Price: 4¢ per call.**
properties_context_mesh_blocks
Mesh-block polygons within 1 km of the property (GeoJSON), each with
avg annual growth, investor counts, modal street and median sold price.
**Price: 30¢ per call.**
properties_context_nearby_for_sale
Currently for-sale listings within `radius_km` of the property
(newest first, max 30) with AVM and rent-yield comparison.
**Price: 20¢ per call.**
properties_context_street_bedroom_series
The subject's bedroom band (bed count from listing history) and the
suburb's 10-year price series for that band.
**Price: 15¢ per call.**
properties_development_all
**Price: 8¢ per call.**
properties_development_zoning_code
Primary zoning at the property's point — code (R2, B4, ...) when
the council ships one, plus the human-readable name and the
broader category.
**Price: 3¢ per call.**
properties_development_zoning_overlays
Development overlays intersecting the property's parcel.
**Price: 5¢ per call.**
properties_history_all
**Price: 80¢ per call.**
properties_neighbours
Adjoining-parcel neighbours, enriched with address + property
type + bed/bath/garage from the latest matching listing.
**Price: 30¢ per call.**
properties_profile
Resolve a GNAF to its full ABS Statistical Geography Standard
hierarchy (Mesh Block → SA1 → SA2 → SA3 → SA4 → GCCSA → State) plus
the parallel admin chain (LGA, suburb (SAL), postcode). Call this
once to get every ABS key the rest of the data layers index on.
**Price: 3¢ per call.**
properties_rent_history
All For Rent records, most-recent first.
**Price: 30¢ per call.**
properties_rent_history_latest
Most-recent For Rent record.
**Price: 10¢ per call.**
properties_risks_all
Every property-level risk overlay in one call. Flat 30¢ — may grow
without increasing the bundle price as new overlays are added.
With ``?geojson=true`` each risk that has a polygon overlay also carries
its 1km-radius-clipped `geojson` FeatureCollection + `geojson_meta`.
**Price: 48¢ per call.**
properties_risks_bushfire
Bushfire-prone-area overlays within 1 km. Read `on_property` — a returned
row means "found nearby", not "this property is in a bushfire zone".
**Price: 15¢ per call.**
properties_risks_environment
Environmental-risk overlay (contamination, salinity, ...).
**Price: 3¢ per call.**
properties_risks_erosion
Coastal / soil erosion overlays within 1 km. Read `on_property` — a
returned row means "found nearby", not "this property is eroding".
**Price: 3¢ per call.**
properties_risks_flood
Modelled flood overlays within 1 km. Read `on_property` — a returned row
means "found nearby", not "this property floods".
**Price: 10¢ per call.**
properties_risks_heritage
Heritage-listing overlays within 1 km. Read `on_property` — a returned row
means "found nearby", not "this property is heritage-listed".
**Price: 3¢ per call.**
properties_risks_historical_flood
Recorded historical flood extents within 1 km. Read `on_property` — a
returned row means "found nearby", not "this property flooded".
**Price: 3¢ per call.**
properties_risks_hv_power_line
High-voltage power-line easement near the parcel.
**Price: 2¢ per call.**
properties_risks_landslide
Landslide-risk overlays within 1 km. Read `on_property` — a returned row
means "found nearby", not "this property is at landslide risk".
**Price: 3¢ per call.**
properties_risks_mobile_black_spot
Mobile-coverage black-spot overlay near the parcel.
**Price: 2¢ per call.**
properties_risks_public_housing
Public-housing concentration overlay near the parcel.
**Price: 4¢ per call.**
properties_sale_history
All Sold + For Sale records, most-recent first.
**Price: 30¢ per call.**
properties_sale_history_latest
Most-recent Sold or For Sale record.
**Price: 10¢ per call.**
properties_schools_all
**Price: 105¢ per call.**
properties_schools_nearby
Schools within ~5km of the property, with rank + student counts.
**Price: 5¢ per call.**
properties_schools_ranking
Schools within ~5km of the property, ranked by NAPLAN / socioeconomic score.
**Price: 100¢ per call.**
properties_street_profile
The property's own street: current median price, 2/4/8-year price
forecasts, realised growth, sale/rental turnover, renter share and
houses/units on the street — plus the suburb-wide medians to judge it
against and the street's rank on 4-year forecast growth.
404s when the street has no forecast row rather than falling back to
suburb-wide figures, which would answer a different question.
**Price: 20¢ per call.**
properties_surroundings_listing_history_signals
Latest sold/rent dates and likely-owner-status signal per nearby property.
**Price: 20¢ per call.**
properties_surroundings_parcels
Cadastral parcel polygons (GeoJSON) for properties around the subject.
**Price: 25¢ per call.**
properties_surroundings_properties
Every GNAF property within 200 m of the subject, with lat/lng and mesh block.
**Price: 15¢ per call.**
properties_surroundings_public_housing
Properties around the subject flagged by the public-housing classifier.
**Price: 15¢ per call.**
properties_surroundings_tenure
ABS Census 2021 tenure shares for each mesh block around the subject.
**Price: 15¢ per call.**
properties_transport_nearby
Nearest train / tram / bus / ferry stop to the property, per mode,
with distance. Widen `radius_m` for the nearest station beyond 1km.
**Price: 5¢ per call.**
properties_valuation_agent_quoting
Quoting accuracy of the property's current listing agency —
cohort, median guide-vs-sold deviation, underquote rate and its 5
most-recent tracked sales. Only while the property is listed for
sale with a tracked agency.
**Price: 50¢ per call.**
properties_valuation_all
**Price: 10¢ per call.**
properties_valuation_avm
Microburbs ML AVM for a single GNAF — point estimate, 80% range,
plus a confidence score (0–100) derived from the interval width.
**Price: 10¢ per call.**
properties_valuation_land_values
Council land valuations for the parcel — val_2021..val_2025 series
with YoY change and $/sqm, plus lot area and zoning description.
**Price: 15¢ per call.**
properties_valuation_negative_gearing
Negative-gearing stat at the finest available level: per-property
cashflow scenarios (80% + 105% LVR), falling back to mesh-block then
suburb investor-exposure.
**Price: 20¢ per call.**
properties_valuation_value_series
Modelled property value over time (monthly for the last year,
annual before that). Houses only — units have no series.
**Price: 30¢ per call.**
area
area_stats_fields
Discover which statistical fields exist. Free (0c). Fuzzy, token-based
matching covers table topics and clean column labels as well as terse field
codes. Common natural-language plurals and Census synonyms are handled, so
the verbatim `query=couples with children` discovers the exact 2021 ABS
family-composition count fields rather than substituting the broader
`census_family_households` metric. Use the returned field code(s) with the
priced `/area-stats/SAL/{suburb}/values` route. ~17k fields available.
**Free.**
area_stats_regions
List the regions that exist at a level — every suburb, LGA, postcode, etc.
Free (0c). Use it to discover the exact region names to pass to /values.
**Free.**
area_stats_values
Statistical field values for one region. Pass `fields` — 1 to 5 field
codes (from /fields) — to fetch.
At SAL level, `mode=sa1` switches from the suburb-aggregate value to a
per-SA1 breakdown — every SA1 that falls inside the suburb, each with its
own values.
**Price: 3¢ per call.**
geocode
geocode_address
Resolve a freeform address string to candidate G-NAF identifiers.
Use this before calling any ``/v1/properties/{gnaf_id}/...`` route —
those endpoints require a GNAF in the path. Returns up to 10
candidates, ranked by Meilisearch score.
**Price: 1¢ per call.**
geocode_suburb
Autocomplete a partial suburb search string against the ABS SAL
list. Use this before calling ``/v1/suburbs/{name}/...`` — those
endpoints require a canonical SAL name in the path.
**Free.**
lga
lga_list
All Australian LGAs. Optional `?state=` filter (e.g. 'NSW').
Returns `{lga, state}` per row. Flat cost.
**Price: 3¢ per call.**
lga_profile
LGA's parent chain — state + GCCSA. LGAs aren't strictly nested
in SA4 so the upward chain stops there.
**Price: 3¢ per call.**
mbs
mbs_list
Mesh-block codes inside a suburb. ``sal`` is required for now —
nationwide / by-LGA / by-SA3 listings will land later when there's
a story for the large payloads (a single LGA can hit a few
thousand mesh blocks).
**Price: 3¢ per call.**
mbs_profile
The mesh block's upward ABS chain — SA1, SA2/3/4, GCCSA, state —
plus the parallel admin chain (LGA, suburb (SAL), postcode).
**Price: 3¢ per call.**
sa4
sa4_list
All Australian SA4s. Optional `?state=` filter. Returns
`{sa4, state}` per row. Flat cost.
**Price: 3¢ per call.**
sa4_profile
SA4's parent chain — GCCSA + state.
**Price: 3¢ per call.**
me
me
Return key identity and the authoritative Autumn credit balance.
**Free.**
ping
ping
Returns immediately if the API is up. No authentication required and not metered — safe to poll from a load balancer, uptime monitor, or status dashboard without affecting your usage.
**Free.**
Tools removed
Tools this server used to expose. Anything built against them stopped working on the day they went.
ping_head
removed 22 Sep 2026
Endpoints
| URL | Transport | State | Latency | Checked |
|---|---|---|---|---|
| https://api.microburbs.com.au/mcp | streamable-http | answering | 1153 ms | 1 min ago |
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Microburbs Australian Property Data — questions
Answers built from our own checks of this server.
What can Microburbs Australian Property Data do?
It exposes 173 tools, read directly from the server on our last check. Among them: area_stats_fields, area_stats_regions, area_stats_values, geocode_address, geocode_suburb, lga_list and 167 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README.
How MCP servers expose tools in the first place →
What is Microburbs Australian Property Data mostly used for?
Its tools cluster around suburbs, properties and area. That is what this server is built to work with — the grouping comes from the actual tool names, not from a category we assigned.
Is Microburbs Australian Property Data working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 89 of 91 checks got a reply (97.8%), average response time 1288 ms. The bar chart above shows every period we have measured.
Did Microburbs Australian Property Data ever remove tools?
Yes. ping_head is no longer exposed — we recorded the date each one disappeared. A tool vanishing usually means a breaking change for anything that depended on it.
How do I connect Microburbs Australian Property Data?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does Microburbs Australian Property Data need an API key?
No. Microburbs Australian Property Data completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 173 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is Microburbs Australian Property Data?
It answers our handshake in 1288 ms on average, which is faster than 6% of all working MCP servers we measure. That is on the slow side — worth knowing if the tool sits inside an interactive loop. The comparison comes from our own checks across the whole registry, every 15 minutes.