Value and compare · Use case

How much rent can I ask for this property?

To set an asking rent, call comps_get-comparables from Casafari's Comparables & Valuation product with operation: rent around the property's address. It returns rental comparables, rent statistics and estimated rents (fast, fair and out-of-market). Then use Area Insights' ma_get_time_series_data with business_type: rent to see how rent per m² has moved in the city.

Products: Comparables & Valuation, Area Insights

#Short answer

comps_get-comparables with operation: rent returns rental comparables, rent statistics and estimated rents (fast_sell_price, fair_market_price and out_of_market_price, computed for the rent operation). Area Insights' ma_get_time_series_data with business_type: rent shows how average rent per m² has moved in the area, so your estimate sits inside a trend.

#Steps

#Call comps_get-comparables with operation rent around the address

1. Call list_servers if you have not used Comparables & Valuation or Area Insights before; it returns each product's instructions.
2. Call comps_get-comparables with operation: "rent", a location_boundary.circle with the address as target_point and a distance in kilometres, comparables_types from one group, and filters such as bedrooms, total_area and characteristics.

#Read rent_price, rent_price_per_sqm, rent_period and rented_at on each comparable

3. In results, read rent_price with rent_currency, rent_price_per_sqm, rent_period, rent_status (active, reserved, hold, rented) and rented_at. rent_price_base and rent_price_per_sqm_base give the same values in euros.

#Resolve the city with ma_get_location_typeahead

4. Call ma_get_location_typeahead with the place name in English, for example "Valencia". Pick the right location_id using administrative_level and breadcrumbs; if several places share the name, add more detail to the query.

#Call ma_get_time_series_data with business_type rent and data_point avg_price_psqm

5. Call ma_get_time_series_data with a request_data object: type_group (apartment or house), business_type: rent, data_point: avg_price_psqm, a date_interval (week, month, quarter, year), date_range.min, an alias, and custom_location_boundary.location_ids (up to 10 ids) or a circle.

#Example: a 2-bedroom flat in Valencia

A landlord asks their assistant: "What is a fair rent for a 2-bedroom flat near Plaza del Ayuntamiento, Valencia?" The assistant calls list_servers, then comps_get-comparables:

{
  "comparables_count": 20,
  "location_boundary": {
    "circle": {
      "target_point": { "address": "Plaza del Ayuntamiento, Valencia" },
      "distance": 1
    }
  },
  "operation": "rent",
  "comparables_types": ["apartment"],
  "bedrooms": 2
}

It then calls ma_get_location_typeahead with "Valencia" and ma_get_time_series_data:

{
  "request_data": {
    "alias": "Valencia",
    "type_group": "apartment",
    "business_type": "rent",
    "data_point": "avg_price_psqm",
    "date_interval": "quarter",
    "date_range": { "min": "2024-01-01" },
    "custom_location_boundary": { "location_ids": ["<location_id from ma_get_location_typeahead>"] }
  }
}

Reading the answer: estimated_prices.fair_market_price is the suggested asking rent and fast_sell_price the figure for letting quickly. Compare fair_market_price_per_sqm with the latest value in the time series (each point has a date_start). A series that keeps rising supports asking nearer the upper estimate; a falling one argues for the fair or fast figure.

#How to read the result

#Check rent_period before comparing prices

rent_period can be day, week, fortnight, month, year or none. Bring every comparable to the same period before comparing rents, and set aside those with none. Casafari's documentation does not state which period the estimated rents are expressed in, so check them against comparables with a monthly rent_period.

#Use sold_or_rented_after to include recent rentals

By default, properties rented since 9 months ago count as comparables, alongside active ones. Set sold_or_rented_after to a YYYY-MM-DD date to change the window, or to null for active properties only. rented_at shows when each comparable was let.

#Gross yield on comparables: the gross_yield field

Each comparable carries gross_yield, a gross yield in percentage, where Casafari has it. To relate your own expected rent to a purchase price, run the same request with operation: sale and compare fair_market_price with twelve months of your estimated rent. See also rentals and commercial coverage and the valuation FAQ.

#Limits

comps_get-comparables and the Area Insights tools are available to Casafari clients with MCP access, using their Casafari account; self-serve access for new users is coming soon. Prices, quotas and rate limits are not published in these docs; ask Casafari. A used-up quota answers Request limit reached for this product.

#Area Insights time series take apartment or house type groups only

type_group accepts apartment or house; send separate requests to compare them. Note the units: the Area Insights circle distance is in metres (50 to 50000), while the comparables circle is in kilometres. A date_range.min that is not a Monday moves to the previous Monday.

#No per-market coverage is stated for these tools

The API's permissions list 16 markets, but neither tool's description names a market, so no per-tool coverage is claimed here. Results depend on the rentals recorded around your target; ma_get_location_typeahead expects English place names.

#Questions

All use cases