Search the aircraft registry
search_aircraftRead-only
Registry-wide aircraft search — the fleet / market-research search surface. Returns individual registered tails matching an AND-combined filter set (make/model, US state, city, year, tail number, current registrant name, on-market status, or geographic radius), with pagination and sorting. Resolve each model name to a make_model_id with search_make_models first; to cover several models in one search pass them as a list with condition "in". For population totals (e.g. "how many R182s in Oregon") prefer count_aircraft, which avoids paging. Each filter is {field_name, condition, value}.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Rows per page, 1–200 (default 25). | |
| offset | No | Pagination offset (default 0). | |
| filters | No | AND-combined filters; each is {field_name, condition, value}. Fields: make_model_id (numeric id), state (2-letter US code), city, year, tail_number, registrant_name (current FAA registrant / registered owner; substring via contains), seen_on_market ("true"/"false"), latest_list_date, location_point, registration_authority, registration_country, airworthiness_class. Conditions: is, is_not, contains, does_not_contain, in, not_in, lt, lte, gt, gte. For location_point use condition "within_<miles>" (e.g. "within_50") with value "lat,lon" (e.g. "45.52,-122.68"). To search SEVERAL make/models at once, use one clause with condition "in" and an array of ids (e.g. {field_name: "make_model_id", condition: "in", value: [1699, 1704]}) — that is a union. Do NOT repeat make_model_id in separate clauses: filters are AND-combined, so two of them match nothing. Spec filters (gt/gte/lt/lte only): engine_power_hp, useful_load_lbs (pounds), smoh_hours (engine hours since major overhaul); engine_make is text (is/contains, e.g. "LYCOMING"). ⚠️ These come from per-model performance specs and listing data and are NOT populated for every aircraft: engine power 75% of the fleet, weights 76%, engine make 78%, smoh_hours only 12% (84% of aircraft that have ever been listed — pair it with seen_on_market). Filtering on one EXCLUDES every aircraft with no value, so tell the user that when you use them. airworthiness_class (is/is_not/in/not_in) is the FAA classification from the aircraft's LATEST registration — this is how you search for EXPERIMENTAL / amateur-built aircraft. Tokens: standard, limited, restricted, experimental, provisional, multiple, primary, special_flight_permit, light_sport. ⚠️ 36% of the fleet has no certification recorded, so filtering on it excludes all of those; say so when you use it. 🔴 STATE OF REGISTRY: this registry is NOT US-only. ~115k aircraft (21.6% of it) are on one of 17 international registers, and they are concentrated by model — 41% of the R44 fleet, 21% of C152s, 10% of SR22s. An unfiltered count is a WORLD count, not a US one. Use registration_authority with an authority code (FAA, TCCA, CASA, ANAC, DGAC, AESA, DGACL, ILT, ACG, IAA, CAANO, NSAT, CAAI, CAABG, CAALV, DAC, CAAS, ECAA) or the cohort tokens "domestic" / "international"; or registration_country with an ISO-2 code or country name ("CA", "Canada"). Say which fleet a number covers whenever you report one. ⚠️ There is NO `country` filter. The v3 validator rejects one (`country` is not a CAVN column), and the underlying value is the FAA registrant's mailing address, NULL for every international aircraft — so it could not select them even if it were accepted. Use registration_country. ⚠️ International aircraft have registry identity but no US market history, so they carry no predicted_price and cannot be valued by tail. | |
| sort_field | No | Sort key (default last_airborne_at). | |
| sort_direction | No | Default desc. |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | Matching registered tails. | |
| meta | Yes |