Airside Labs builds and validates AI for travel and aviation, advises startups, and publishes open benchmarks — including the Pre-Flight aviation benchmark.
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Last probed Nov 3, 2026 · mcp.airsidelabs.com
27tools discovered
For AI agents — MCPBundles Directory API
For MCP client apps (human connect):
MCP connect URL: https://mcp.airsidelabs.com/mcp
Skill page: https://www.mcpbundles.com/skills/airsidelabs-mcp-331b6049b0
Explore capabilities (27)
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write 1
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Airport6
Resolve4
Get2
Trace2
Other capabilities11
Resolve airport
read
resolve_airport
Which aerodrome does this airport code or name refer to on a given date?
Accepts an IATA three-letter code, an ICAO four-letter code, an airport
name fragment or a city name. Returns the aerodrome with its codes,
location, elevation, IANA timezone and type (large, medium, small,
heliport or closed).
Pass `as_of` whenever the question concerns a past date. Airport codes move
between aerodromes: ATH meant Ellinikon until 2001 and Athens
International after it; HKG meant Kai Tak until 1998. Witho
Description may be truncated on the public preview.
Resolve airport — Which aerodrome does this airport code or name refer to on a given date?
Accepts an IATA three-letter code, an ICAO four-letter code, an airport
name fragment or a city name. Returns the aerodrome with its codes,
location, elevation, IANA timezone and type (large, medium, small,
heliport or closed).
Pass `as_of` whenever the question concerns a past date. Airport codes move
between aerodromes: ATH meant Ellinikon until 2001 and Athens
International after it; HKG meant Kai Tak until 1998. Witho
Resolve airline — Which airline does this designator, name or callsign refer to on a date?
Accepts an IATA two-character designator, an ICAO three-letter designator,
an airline name or a callsign. Returns the operator with both designators,
country, operational status and, where an airline ceased, its successor.
`as_of` matters more here than for any other tool. IATA two-character
designators are heavily reused: SN was Sabena until 2001 and has been
Brussels Airlines since 2007, so "SN" without a date is a ques
Resolve aircraft type — Which aircraft type does this designator or marketing name refer to?
Accepts an ICAO type designator (A21N) or a marketing name people actually
say ("A321neo", "Dash 8-400", "777-300ER", "Q400"). Returns the ICAO
designator, manufacturer, model, engine count and type, aircraft class, and
the ICAO wake turbulence category.
A name that identifies a family rather than a variant -- "Dreamliner",
"777X", "A330neo" -- returns `ambiguous` with the variants as alternates
and a confidence in the 0.4-0.
Resolve registration — Which airframe wore this registration on a given date?
Accepts a tail number in any common form: VH-OQA, VHOQA, lowercase, padded
with whitespace. Returns the aircraft with its country of registry, ICAO
type designator, an embedded resolved aircraft type, operator, owner,
serial number and Mode-S hex address.
A registration is a slot rather than a permanent name: marks are
surrendered and reissued. N803AL was one airframe from 1987 to 1993 and a
different one, a 787-8, from 2015; N264CP moved
Parse flight identifier — Split a flight designator into carrier and number, and identify the carrier.
Accepts the forms that arrive in real message traffic: TK1979, BAW276,
"U2 8341", BA02490, BA2490A. Returns the parsed carrier with its resolved
airline, the flight number, any operational suffix, which scheme was used
(IATA or ICAO), and both normalised forms.
Two things this tool will not do. It will not tell you who operated the
flight: a designator names the marketing carrier, and a codeshare is
invisible in the s
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What is the Airside Labs | AI Systems for Travel & Aviation MCP server?
Airside Labs builds and validates AI for travel and aviation, advises startups, and publishes open benchmarks — including the Pre-Flight aviation benchmark.
How do I connect Airside Labs | AI Systems for Travel & Aviation to my AI agent?
Use the MCP endpoint listed on this page in your MCP client configuration. One-click install pills support Claude, Cursor, VS Code, and other hosts. Copy the remote MCP URL if your client needs a manual entry.
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Flight airframes — Which airframes have been heard operating this airline flight, how often and when --
from Airside Labs' own ADS-B receiver?
Accepts a flight in any common form: BA49, BAW49, "BA 49", VS105. Returns each airframe
heard broadcasting that Flight ID within the receiver's footprint, with its Mode-S
address, registration and ICAO type (joined from the registrations dataset), how many
receiver poll cycles it was in view for, over how many distinct days, and first and last
heard. `most_seen` and `most_
Validate identifiers — Do these aviation identifiers describe the same thing on this date?
Give any combination of a registration (tail number), a Mode-S 24-bit
address, an ICAO type designator, an operator name, an airline designator
(IATA or ICAO), a callsign and a flight designator, plus `as_of`. Each
pair that can be checked is checked, and every check comes back with a
verdict -- `consistent`, `contradicted` or `unverifiable` -- the detail,
and the rule that decided it. `contradictions` lists the failures on
the
Report unmet need — Tell us what you came looking for and could not get from these tools.
Call this when you needed something aviation-related that this toolset did
not give you. It is not an error channel and it is not a retry: it is how
the next version of these tools learns what is missing. A need reported
here is read by a person.
Use it when:
- a tool returned `unresolved` and you believe the thing exists
- a tool returned `ambiguous` and nothing available could break the tie
- the entity resolved but
Use-case landscape — How many use cases are there, sliced one way? Counts you can quote.
`group_by` is one of org_type (16 canonical organisation types: Airport,
Airline, Air Navigation Service Provider, Ground Handling, Regulator /
Authority, Aerospace Manufacturing, MRO / Maintenance …), sector, role
(500+ roles), ai_level, hazard_class, or cadence_class (counts data
requirements rather than use cases). Filters AND together and apply
before grouping, so group_by=role with org_type=Airport lists airport
roles by h
Search use cases — Which aviation AI use cases match this text? Find candidates by keyword.
Full-text search (BM25, stemmed) over 6,500 use cases spanning airports,
airlines, ANSPs, ground handlers, regulators, manufacturers and more, each
attached to a role and an organisation type. Returns summaries only --
id, short text, role, organisation type, EASA screen -- capped at 25.
Use get_use_case for the full record with its data requirements.
Search concrete operational nouns ("stand allocation", "baggage
misconn
Get use case — The full record for one use case, by id from a search or landscape result.
Returns the use-case text; the role that owns it with its description; the
organisation type (canonical and as the corpus names it); every data
requirement -- title, description, nominal update rate with a normalised
cadence class (real_time … annual), and the kind of system it typically
comes from; the EASA screen (AI level, hazard class, confidence, rationale)
with the framework rows it points at, page-cited; keywords;
Similar use cases — What else in the catalogue is like this use case? Nearest neighbours by meaning.
Returns up to 20 use cases closest in embedding space (bge-base cosine
over the use-case text), as summaries with a `similarity`. Good for "what
else is like the one we picked", for finding the same idea stated for a
different role or organisation type, and for spotting near-duplicates
before counting them as two.
Similarities are compressed into roughly 0.5-0.95: rank within one result,
never threshold across the
Data requirements — What data does this use case, role or organisation type need, and how fresh?
Three modes. With `use_case_id`: that use case's requirements verbatim --
title, normalised title_family, description, nominal update rate,
normalised cadence class and the kind of source system. With `query`:
REVERSE lineage -- full-text search over requirement titles and
descriptions (the inputs, not the use-case text), returning the use cases
that CONSUME data matching the query. Ask `query="taxi-out time"` to get
e
Trace data lineage — Which standard operational messages would evidence this data need?
The lineage spine is use case -> data requirement -> requirement family ->
standard message type -> data elements. Four modes. With `use_case_id`:
that use case's requirements grouped by family, each family with the
standard messages that evidence it (relevance primary/supporting, cadence,
element count) -- plus `requirements_without_standard_messages`, the needs
no standard message covers, which is the honest feed-gap statement
Trace operational workflow — What happens before and after this use case, and who hands off to whom?
The catalogue is otherwise flat -- role, use case, data requirement -- with
no edges. This is the edges: named operational sequences with their steps in
order, the role at each step, the `gate` that must hold before the next one
may start, and what passes between roles at each handoff (headset, radio,
hand signal, system, visual, document, verbal, formal correspondence).
Three modes. With `use_case_id`: every workflow that
EASA AI framework screen — The EASA AI-level and hazard-class tables, page-cited, to read a screen against.
Returns the AI levels (0, 1A, 1B, 2A, 2B, 3A, 3B: what the system does and
how much authority the end user keeps), the hazard classes (H1-H5: worst
credible effect and the assurance level it implies at acceptable and
moderate risk), the technique ceilings (which AI techniques the Concept
Paper accepts up to which level), and source notes. Pass `level` or
`hazard_class` for one row. Every row carries `cp_ref`, the p
List real-day scenarios — Which real operational episodes does the catalogue carry, to illustrate use cases with?
A scenario is one real day reconstructed from data Airside Labs holds and
may publish: FAA SWIM flight plans, FAA NOTAMs, its own ADS-B receiver. Each
is a UTC window at a place, a timeline whose every event names the raw
record it came from, and a set of lenses -- one use case's cut of the day,
with the actual rows, an implication, and the use cases it is attached to.
This lists them with their window, plac
Get a real-day scenario — One real episode end to end: what happened, where and when (UTC), the actors,
what it shows and what it must not be read as; the timeline, every event with its
actor, source and the reference of the raw record it came from; and the lenses,
each a use case's cut of the day with a small evidence table, an implication, and
the use cases it illustrates with a reason for each.
Use it when a brief needs the whole story rather than one finding: a
worked example with a paper trail, an edge-case write-u
Airport network integration — What level of network integration does this airport have with the EUROCONTROL Network
Manager, or with the FAA's TFDM programme, as of a date?
Answers with one value: `ani` (Advanced Network Integrated: A-CDM with the higher level of
integration), `acdm` (all DPI message types sent to the network, so a TOBT and TSAT stream
exists), `adv_twr` (Advanced ATC TWR: E-DPI, C-DPI and A-DPI only, no TOBT or TSAT stream),
`tfdm_a` or `tfdm_b` (FAA Terminal Flight Data Manager configurations), `standard`
Airport operator — Who operates this airport, which group would take the commercial meeting, and who owns
it?
Returns operator_name, operator_group (the parent that a sales or partnership conversation
lands with, spelled consistently: Aena, MAG, Groupe ADP, Fraport, VINCI Airports, Adani and
so on), ownership_class (public-national, public-regional, private-group,
private-individual, concession-mixed or unknown), owner_name, concession_end_year where a
public page states it, and the listed parent and ticker where
Airport operations status — Is there a positive, sourced reason this airport is not open for ordinary commercial
engagement: closed to civil traffic, in a sanctioned jurisdiction, or a general-aviation
field with no scheduled service?
Returns `closed` (no civil passenger operations), `restricted` (the airport operates but
sits under UK sanctions guidance for its jurisdiction, with the guidance page cited),
`general-aviation` (no scheduled passenger service), or `no_exception_recorded`. The last
is exactly that: this datas
Airport connectivity — How many nonstop destinations does this airport publish, and in which countries?
Returns the count of nonstop destinations from the airport's published destination table,
the number resolved to a country, the destinations by country, and the counts to the United
States, the Gulf and the UAE, with the date of the read.
This is presence, not frequency: one weekly seasonal service and a daily trunk route count
the same. It is right for "does this airport connect to the US at all" and wrong for
"h
Airport size band — Which ACI passenger size band is this airport in, on its latest published annual total?
Returns the passengers figure, its year, and the band on ACI World's published ASQ size
categories: under 2M, 2 to 5M, 5 to 15M, 15 to 25M, 25 to 40M, over 40M passengers per year.
The figure comes from the airport's Wikipedia infobox (its latest published annual total),
not from ACI, so airports are not on a common year; the year travels with the answer, and a
figure dated the current year is flagged as pro
Route capacity — How much scheduled capacity is flown nonstop from one airport to another, by whom and
on what, over the last N months of BTS T-100 data?
Returns monthly departures performed, seats and passengers with the load factor, and the
same broken down by carrier and aircraft type with seats per departure and the sector
distance (BTS statute miles, and nautical miles converted). The pair is DIRECTIONAL:
SEA to LHR is not LHR to SEA; ask both if you need the round trip. `months` defaults to
the last 12 of
Airport fleet mix — What aircraft types fly from (or into) an airport, how often, with how many seats, and
at what load factor, over the last N months of BTS T-100 data?
Returns each type's departures performed and share of the airport's departures, seats,
passengers, load factor, seats per departure, and how many carriers and destinations it
serves, plus airport totals. `direction` is `departures` (default) or `arrivals`.
`months` defaults to the last 12 of the window; pass null for the whole window.
Scheduled pa
Showing the first 25 tools — full list and schemas: Directory API.
How many tools does Airside Labs | AI Systems for Travel & Aviation provide?
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