American Airlines
American Airlines is one of the world's largest airlines, operating an extensive domestic and international route network. The company's Runway developer experience platform, built on Spotify's Backstage, provides internal developer tooling and API management for engineering teams. American Airlines exposes flight data, status, and booking capabilities through its developer portal, and maintains an active open-source presence via the AmericanAirlines GitHub organization.
Limited machine-readable signal and partial portal coverage — documentation a human can read, but little a machine or agent can consume without scraping.
API Evangelist profiles American Airlines the way a machine reads it — 41 machine-readable artifacts across 2 APIs, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — American Airlines scores 44.5/100 (thin), with a separate agent-readiness read of 39/100 (agent aware). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.
Kin Score
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile American Airlines
Each block below is one kind of artifact we hold for American Airlines. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
APIs 2
Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.
Individual APIs this provider publishes, each with its own machine-readable definition.
American Airlines Bookings API
Booking management operations
American Airlines Flights API
Flight information and status operations
Open Collections 1
Open, tool-agnostic collections carry the same runnable value as Postman without locking you to one client — the portable, forkable form of the same exercise.
Open, tool-agnostic API collections (OpenAPI-derived and Bruno).
American Airlines Runway Developer API
OPEN COLLECTIONGraphQL 1
Where a provider ships GraphQL, the schema is the contract. We profile it alongside the REST surface so the whole interface is legible in one place.
GraphQL schemas published by this provider.
American Airlines GraphQL Schema
This conceptual GraphQL schema models the American Airlines travel and flight API domain. It covers the full lifecycle of air travel including flight search, booking, reservatio...
GRAPHQLPricing Plans 1
Pricing is part of the interface. Machine-readable plans tell you what a tier costs and includes before you commit — one of the six things the Kin Score reads for commercial clarity.
Published pricing tiers and plan structures.
Rate Limits 1
Rate limits are the difference between a demo that works and a production integration that doesn't fall over. Publishing them is an operational-transparency signal — and a hard requirement for any agent that plans its own throughput.
Documented rate limits and quota policies.
American Airlines Rate Limits
RATE LIMITSFinOps 1
Cost, billing, and metering signals let a buyer model the financial operations of an API before it's live. We profile them for the same reason we profile pricing: the money is part of the contract.
Cost, billing, and metering signals for API financial operations.
American Airlines Finops
FINOPSFeatures 6
The notable capabilities this provider advertises, captured as structured features so they can be searched and compared instead of read one landing page at a time.
Notable capabilities this provider offers.
Runway Developer Experience Platform
Internal developer platform built on Spotify's Backstage providing centralized API management, service catalog, and self-service infrastructure tooling for engineering teams.
Flight Data APIs
APIs for querying flight schedules, routes, status information, and operational data across American Airlines' domestic and international network.
Booking and Reservation APIs
APIs supporting flight search, booking, reservation management, and passenger services integration for travel applications.
Built-In API Management
Runway provides integrated API management with security, authentication toggles, and corporate authentication capabilities for development teams.
Service Mesh Integration
Kong-based service mesh enabling reliable microservices communication and traffic management across the American Airlines platform.
Open Source Tooling
American Airlines maintains open-source tools including Flight Engine (mock flight data API), Hangar (hackathon management), and Backstage plugins via the AmericanAirlines GitHu...
Semantic Vocabularies 1
JSON-LD contexts give the data shared meaning across APIs. We profile them because semantics are what let a machine reconcile 'customer' here with 'customer' somewhere else.
JSON-LD contexts and semantic vocabularies used across these APIs.
Spectral Rules 2
Governance rulesets we run against this provider's specs — the automated checks behind parts of the score. Profiling them makes the quality bar explicit and re-runnable, not a matter of opinion.
American Airlines API Rules
SPECTRALAmerican Airlines API Rules
SPECTRALJSON Schema 5
Standalone JSON Schema definitions describe the data models behind the API. We profile them so the shapes are validatable on their own — useful long after a single request is forgotten.
Standalone JSON Schema definitions for this provider's data models.
BookingRequest
JSON SCHEMABooking
JSON SCHEMAFlightList
JSON SCHEMAFlight
JSON SCHEMAFlightStatus
JSON SCHEMAJSON Structure 5
JSON Structure captures the data shapes in a form built for tooling — a complement to JSON Schema that keeps the model machine-legible.
JSON Structure definitions describing this provider's data shapes.
Runway Developer Api Booking Request Structure
JSON STRUCTURERunway Developer Api Booking Structure
JSON STRUCTURERunway Developer Api Flight List Structure
JSON STRUCTURERunway Developer Api Flight Status Structure
JSON STRUCTURERunway Developer Api Flight Structure
JSON STRUCTUREExamples 5
Real request and response payloads are what turn a spec from abstract into obvious — and they're one of the twelve things an agent needs to call an API correctly on the first try.
Example request and response payloads for these APIs.
Security Posture 1
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Agentic Access 1
An x-agentic-access contract marks which operations are safe for an agent to run on its own and which need a human in the loop. It is the difference between an API an agent can use and one it can use safely.
Recommended x-agentic-access execution contracts for AI agents.
Use Cases 4
What developers actually build with this provider — captured so the catalogue answers 'what is this for', not just 'what does this expose'.
What developers build with this provider.
Flight Search and Booking
Travel agencies and booking platforms integrate flight availability, pricing, and reservation APIs to offer American Airlines flights.
Flight Status Tracking
Applications query real-time flight status, departure, arrival, and delay information for American Airlines flights.
Internal Developer Tooling
American Airlines engineering teams use Runway to self-service infrastructure, register APIs in the service catalog, and manage deployments.
Hackathon and Innovation
Open-source Hangar tool enables hackathon management for tech innovation events sponsored by or affiliated with American Airlines.
Integrations 4
Pre-built integrations with other platforms tell you where this provider already fits in a stack.
Pre-built integrations with other platforms and tools.
Spotify Backstage
Runway developer portal is built on Spotify's Backstage platform for internal developer experience and service catalog management.
Kong Service Mesh
American Airlines uses Kong's Kuma service mesh for microservices networking and API gateway capabilities.
HashiCorp Vault
Integration with HashiCorp Vault for secrets management in build pipelines via open-source vault-action GitHub Action.
Dynatrace
Python API client for Dynatrace integration maintained in the AmericanAirlines GitHub organization.
Resources
Every other property we hold for American Airlines — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Get Started 1
Portal, sign-up, and the first successful call
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Build 4
SDKs, sample code, and the tooling you integrate with
Access & Security 1
Authentication, authorization, and security posture
Company 3
The organization behind the API
← All providers · Data indexed from github.com/api-evangelist/american-airlines · machine-readable index on apis.io