Understand an area · Use case

What does a 2-bedroom apartment cost in this area, and how are prices spread?

Casafari Area Insights answers both questions over MCP. area-insights_get_bedrooms_distribution returns properties_count, average_price and average_price_per_sqm for each bedroom count in an area, so you read the 2-bedroom row directly. area-insights_get_price_distribution returns the number of properties in each price interval, with is_mean marking the band that holds the mean price.

Products: Area Insights

#Short answer

Two Area Insights tools answer this question.

area-insights_get_bedrooms_distribution returns one row per bedroom count, with:

• bedrooms (a label).
• properties_count.
• average_price.
• average_price_per_sqm.

area-insights_get_price_distribution returns one row per price interval, with:

• lower_bound and upper_bound.
• properties_count.
• is_mean, which is true for the band that holds the mean price.

Together they give the going price for each bedroom count and show where supply sits across price bands.

#Steps

#Resolve the area

1. Call locations_search with an English place name, for example Malaga, and keep the location_id. Use the breadcrumbs to make sure it is the city you mean.

#Call area-insights_get_bedrooms_distribution with type_group, business_type, bedrooms_range (0 to 10)

2. Call area-insights_get_bedrooms_distribution with a request_data object.
   • Required: type_group (apartment or house), business_type (sale or rent) and custom_location_boundary.
   • Optional: bedrooms_range (min and max from 0 to 10), plus price_range, total_area_range, conditions and exclude_outliers (default true).

#Call area-insights_get_price_distribution with the same boundary and an optional price_range

3. Call area-insights_get_price_distribution with the same type_group, business_type and custom_location_boundary. Add a price_range to focus on one window, for example 200,000 to 300,000.

#Over REST, POST /market-analytics-api/distributions/properties for the properties distribution

4. Over REST, send POST /market-analytics-api/distributions/properties. Its body takes:

   • types, business_type and custom_location_boundary.
   • Range filters (price_range, price_per_sqm_range, rooms_range, bedrooms_range, bathrooms_range, total_area_range, plot_area_range, construction_year_range).
   • characteristics, conditions, private, bank, auction and exclude_outliers.

   Its response fields are documented on the operation page.

#Example: apartments for sale in Málaga

Prompt to the assistant: "What does a 2-bedroom apartment for sale in Málaga cost, and how many apartments are priced between 200,000 and 300,000?"

The assistant calls locations_search (Malaga), then area-insights_get_bedrooms_distribution:

{
  "request_data": {
    "type_group": "apartment",
    "business_type": "sale",
    "custom_location_boundary": {"location_ids": [MALAGA_LOCATION_ID]},
    "bedrooms_range": {"min": 1, "max": 4}
  }
}

Then it calls area-insights_get_price_distribution:

{
  "request_data": {
    "type_group": "apartment",
    "business_type": "sale",
    "custom_location_boundary": {"location_ids": [MALAGA_LOCATION_ID]},
    "price_range": {"min": 200000, "max": 300000}
  }
}

For the cost question, it reads the row where bedrooms is 2: average_price and average_price_per_sqm, with properties_count as the sample size. For the count question, it sums properties_count across the returned bands and notes which band has is_mean set. The figures come from the live calls; these docs publish none.

#How to read the result

#Bedroom rows for segmentation and unit mix

Use the bedroom rows in two ways:

• Pricing: compare a property's asking price per m² with average_price_per_sqm for its bedroom count.
• Supply mix: properties_count by bedroom count shows the mix of stock on offer. Developers can compare that mix with the units they plan.

#Price bands: where supply concentrates and where the mean sits

The bands with the highest properties_count are where competition for buyers is strongest. The band with is_mean true holds the mean price. A property priced far above it competes with less, and usually different, stock. An upper_bound of null marks the open top band.

#Limits

Availability:

• Both MCP tools are self-serve on the Casafari API and MCP Platform.
• Existing Casafari clients sign up there too; contract clients are set up on the Custom plan. The REST operation also stays available to Casafari clients with their Casafari account.
• POST /market-analytics-api/distributions/properties is REST only and also self-serve.

Coverage:

• The tool descriptions name no specific market.
• Only the apartment and house type groups are accepted.

Pricing and quotas:

• The sources give no figures for pricing or quotas. Ask Casafari.

#bedrooms_range in the bedrooms distribution is capped at 10

In area-insights_get_bedrooms_distribution, bedrooms_range.min and bedrooms_range.max accept 0 to 10. Other Area Insights tools accept higher values.

#Boundaries are location ids (up to 10) or a circle

custom_location_boundary takes either location_ids (1 to 10) or a circle. A circle has a target_point and a distance of 50 to 50,000 metres. Polygons are not accepted by these MCP tools. See location ids.

#Questions

All use cases