Apache Airflow
Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows, developed by the Apache Software Foundation. It allows you to define workflows as Directed Acyclic Graphs (DAGs) in Python code, making them maintainable, versionable, testable, and collaborative. Airflow provides a stable REST API for managing DAGs, DAG runs, tasks, connections, variables, pools, and users, along with a web-based UI for monitoring and managing pipeline execution.
Solid contracts, transparent operations, and an easy start — typically complete on four or five facets with one clear soft spot.
API Evangelist profiles Apache Airflow the way a machine reads it — 265 machine-readable artifacts across 19 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 — Apache Airflow scores 62.5/100 (strong), with a separate agent-readiness read of 66/100 (agent native). 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 Apache Airflow
Each block below is one kind of artifact we hold for Apache Airflow. 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 19
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.
Apache Airflow Experimental API (Deprecated)
The experimental API that preceded the stable REST API. This is deprecated and should not be used for new implementations.
Apache Airflow Config API
The Config API from Apache Airflow — 1 operation(s) for config.
Apache Airflow Connection API
The Connection API from Apache Airflow — 3 operation(s) for connection.
Apache Airflow DAG API
The DAG API from Apache Airflow — 8 operation(s) for dag.
Apache Airflow DAGRun API
The DAGRun API from Apache Airflow — 6 operation(s) for dagrun.
Apache Airflow DagWarning API
The DagWarning API from Apache Airflow — 1 operation(s) for dagwarning.
Apache Airflow Dataset API
The Dataset API from Apache Airflow — 4 operation(s) for dataset.
Apache Airflow EventLog API
The EventLog API from Apache Airflow — 2 operation(s) for eventlog.
Apache Airflow ImportError API
The ImportError API from Apache Airflow — 2 operation(s) for importerror.
Apache Airflow Monitoring API
The Monitoring API from Apache Airflow — 2 operation(s) for monitoring.
Apache Airflow Permission API
The Permission API from Apache Airflow — 1 operation(s) for permission.
Apache Airflow Plugin API
The Plugin API from Apache Airflow — 1 operation(s) for plugin.
Apache Airflow Pool API
The Pool API from Apache Airflow — 2 operation(s) for pool.
Apache Airflow Provider API
The Provider API from Apache Airflow — 1 operation(s) for provider.
Apache Airflow Role API
The Role API from Apache Airflow — 2 operation(s) for role.
Apache Airflow TaskInstance API
The TaskInstance API from Apache Airflow — 9 operation(s) for taskinstance.
Apache Airflow User API
The User API from Apache Airflow — 2 operation(s) for user.
Apache Airflow Variable API
The Variable API from Apache Airflow — 2 operation(s) for variable.
Apache Airflow XCom API
The XCom API from Apache Airflow — 2 operation(s) for xcom.
Scroll within the panel for all 19 ·
Arazzo Workflows 13
Real integrations are rarely a single call. Arazzo describes the multi-step sequences — auth, then create, then confirm — so both a human and an agent can follow the choreography, not just the endpoints.
Multi-step API workflows described with the Arazzo specification.
Apache Airflow Audit DAG Runs Across the Fleet
Use the batch endpoints to pull failed runs and their task instances across many DAGs in a date window, then check the event log for who intervened.
ARAZZOApache Airflow Collect DAG Run Results from XCom
Wait for a DAG run to finish, find the producing task instance, and pull its XCom return value.
ARAZZOApache Airflow Trace Dataset-Driven Lineage
Find a dataset by URI, read the tasks that produce it and the DAGs that consume it, and trace the events that triggered a downstream run.
ARAZZOApache Airflow Deployment Preflight Check
Verify scheduler and metadatabase health, capture the version, and surface DAG import errors and warnings before trusting a deployment.
ARAZZOApache Airflow Diagnose a Failed DAG Run
Isolate the failed task in a DAG run, pull its logs for the last attempt, and record the diagnosis as a note.
ARAZZOApache Airflow Force a Task Instance State
Preview and then set a task instance's state to unblock a stuck pipeline, verifying the DAG run recovers.
ARAZZOApache Airflow Onboard a DAG
Orient on an unfamiliar DAG by reading its metadata, schedule details, task graph, source code, and recent run history.
ARAZZOApache Airflow Provision a User with a Role
Ensure a role exists with the intended permissions, create a user bound to it, and verify the assignment.
ARAZZOApache Airflow Register a Connection After Testing It
Test a connection's credentials against the target system before saving it, then create and verify the stored connection.
ARAZZOApache Airflow Retry Failed Tasks in a DAG Run
Preview which task instances a clear would touch, clear the failed ones for real, and wait for the re-run to settle.
ARAZZOApache Airflow Trigger a DAG Run and Wait for Completion
Unpause a DAG if needed, trigger a run with a configuration payload, and poll until the run reaches a terminal state.
ARAZZOApache Airflow Upsert a Slot Pool
Create or resize an Airflow pool by name, then read back its slot accounting.
ARAZZOApache Airflow Upsert a Variable
Look up an Airflow variable and update it if it exists, otherwise create it, then read the result back.
ARAZZOScroll within the panel for all 13 ·
MCP Servers 1
Model Context Protocol servers expose these APIs directly to AI agents. We profile them because agent-native access is the fastest-growing way this provider's capabilities actually get used.
Model Context Protocol servers that expose these APIs to AI agents.
apache-airflow-mcp.yml
MCP SERVERPricing 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.
Apache Airflow 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.
Apache Airflow Finops
FINOPSFeatures 10
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.
DAG-as-Code
Define workflows as Python code (Directed Acyclic Graphs) for version control, testing, and collaboration.
Stable REST API
Full-featured REST API for programmatic management of DAGs, runs, tasks, connections, variables, pools, and users.
Dynamic Pipeline Generation
Generate DAGs dynamically using Python, supporting complex conditional and parametric pipelines.
Extensible Providers
Rich ecosystem of provider packages for integrating with AWS, GCP, Azure, databases, and hundreds of external services.
Rich Web UI
Browser-based dashboard for monitoring DAG runs, task statuses, logs, and Gantt charts.
Resource Pools
Control concurrency and resource allocation across tasks using configurable pools.
Cross-DAG Dependencies
Define dependencies between DAGs using sensors, dataset-driven scheduling, and external task sensors.
Pluggable Executors
Supports Sequential, Local, Celery, Kubernetes, and DASK executors for flexible deployment.
SLA Monitoring
Define and track Service Level Agreements on task and DAG completion times.
Variable and Connection Management
Centrally manage environment-specific configuration via Airflow variables and connections.
Scroll within the panel for all 10 ·
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.
Apache Airflow Context
JSON-LDSpectral 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.
Apache Airflow API Rules
SPECTRALApache Airflow API Rules
SPECTRALJSON Schema 84
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.
ActionCollection
JSON SCHEMAActionResource
JSON SCHEMAAction
JSON SCHEMABasicDAGRun
JSON SCHEMAClassReference
JSON SCHEMAClearDagRun
JSON SCHEMAClearTaskInstances
JSON SCHEMACollectionInfo
JSON SCHEMAColor
JSON SCHEMAConfigOption
JSON SCHEMAConfig
JSON SCHEMAConfigSection
JSON SCHEMAConnectionCollectionItem
JSON SCHEMAConnectionCollection
JSON SCHEMAConnection
JSON SCHEMAConnectionTest
JSON SCHEMACronExpression
JSON SCHEMADAGCollection
JSON SCHEMADAGDetail
JSON SCHEMADAGRunCollection
JSON SCHEMADAGRun
JSON SCHEMADagScheduleDatasetReference
JSON SCHEMADAG
JSON SCHEMADagState
JSON SCHEMADagWarningCollection
JSON SCHEMADagWarning
JSON SCHEMADatasetCollection
JSON SCHEMADatasetEventCollection
JSON SCHEMADatasetEvent
JSON SCHEMADataset
JSON SCHEMAEventLogCollection
JSON SCHEMAEventLog
JSON SCHEMAExtraLinkCollection
JSON SCHEMAExtraLink
JSON SCHEMAHealthInfo
JSON SCHEMAHealthStatus
JSON SCHEMAImportErrorCollection
JSON SCHEMAImportError
JSON SCHEMAJob
JSON SCHEMAListDagRunsForm
JSON SCHEMAListTaskInstanceForm
JSON SCHEMAMetadatabaseStatus
JSON SCHEMAPluginCollectionItem
JSON SCHEMAPluginCollection
JSON SCHEMAPoolCollection
JSON SCHEMAPool
JSON SCHEMAProviderCollection
JSON SCHEMAProvider
JSON SCHEMARelativeDelta
JSON SCHEMAResource
JSON SCHEMARoleCollection
JSON SCHEMARole
JSON SCHEMAScheduleInterval
JSON SCHEMASchedulerStatus
JSON SCHEMASetDagRunNote
JSON SCHEMASetTaskInstanceNote
JSON SCHEMASLAMiss
JSON SCHEMATag
JSON SCHEMATaskCollection
JSON SCHEMATaskInstanceCollection
JSON SCHEMATaskInstanceReferenceCollection
JSON SCHEMATaskInstanceReference
JSON SCHEMATaskInstance
JSON SCHEMATaskOutletDatasetReference
JSON SCHEMATask
JSON SCHEMATaskState
JSON SCHEMATimeDelta
JSON SCHEMATimezone
JSON SCHEMATriggerRule
JSON SCHEMATrigger
JSON SCHEMAUpdateDagRunState
JSON SCHEMAUpdateTaskInstance
JSON SCHEMAUpdateTaskInstancesState
JSON SCHEMAUserCollectionItem
JSON SCHEMAUserCollection
JSON SCHEMAUser
JSON SCHEMAVariableCollectionItem
JSON SCHEMAVariableCollection
JSON SCHEMAVariable
JSON SCHEMAVersionInfo
JSON SCHEMAWeightRule
JSON SCHEMAXComCollectionItem
JSON SCHEMAXComCollection
JSON SCHEMAXCom
JSON SCHEMAScroll within the panel for all 84 ·
JSON Structure 84
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.
Openapi.Yaml Action Collection Structure
JSON STRUCTUREOpenapi.Yaml Action Resource Structure
JSON STRUCTUREOpenapi.Yaml Action Structure
JSON STRUCTUREOpenapi.Yaml Basic Dag Run Structure
JSON STRUCTUREOpenapi.Yaml Class Reference Structure
JSON STRUCTUREOpenapi.Yaml Clear Dag Run Structure
JSON STRUCTUREOpenapi.Yaml Clear Task Instances Structure
JSON STRUCTUREOpenapi.Yaml Collection Info Structure
JSON STRUCTUREOpenapi.Yaml Color Structure
JSON STRUCTUREOpenapi.Yaml Config Option Structure
JSON STRUCTUREOpenapi.Yaml Config Section Structure
JSON STRUCTUREOpenapi.Yaml Config Structure
JSON STRUCTUREOpenapi.Yaml Connection Collection Item Structure
JSON STRUCTUREOpenapi.Yaml Connection Collection Structure
JSON STRUCTUREOpenapi.Yaml Connection Structure
JSON STRUCTUREOpenapi.Yaml Connection Test Structure
JSON STRUCTUREOpenapi.Yaml Cron Expression Structure
JSON STRUCTUREOpenapi.Yaml Dag Collection Structure
JSON STRUCTUREOpenapi.Yaml Dag Detail Structure
JSON STRUCTUREOpenapi.Yaml Dag Run Collection Structure
JSON STRUCTUREOpenapi.Yaml Dag Run Structure
JSON STRUCTUREOpenapi.Yaml Dag Schedule Dataset Reference Structure
JSON STRUCTUREOpenapi.Yaml Dag State Structure
JSON STRUCTUREOpenapi.Yaml Dag Structure
JSON STRUCTUREOpenapi.Yaml Dag Warning Collection Structure
JSON STRUCTUREOpenapi.Yaml Dag Warning Structure
JSON STRUCTUREOpenapi.Yaml Dataset Collection Structure
JSON STRUCTUREOpenapi.Yaml Dataset Event Collection Structure
JSON STRUCTUREOpenapi.Yaml Dataset Event Structure
JSON STRUCTUREOpenapi.Yaml Dataset Structure
JSON STRUCTUREOpenapi.Yaml Event Log Collection Structure
JSON STRUCTUREOpenapi.Yaml Event Log Structure
JSON STRUCTUREOpenapi.Yaml Extra Link Collection Structure
JSON STRUCTUREOpenapi.Yaml Extra Link Structure
JSON STRUCTUREOpenapi.Yaml Health Info Structure
JSON STRUCTUREOpenapi.Yaml Health Status Structure
JSON STRUCTUREOpenapi.Yaml Import Error Collection Structure
JSON STRUCTUREOpenapi.Yaml Import Error Structure
JSON STRUCTUREOpenapi.Yaml Job Structure
JSON STRUCTUREOpenapi.Yaml List Dag Runs Form Structure
JSON STRUCTUREOpenapi.Yaml List Task Instance Form Structure
JSON STRUCTUREOpenapi.Yaml Metadatabase Status Structure
JSON STRUCTUREOpenapi.Yaml Plugin Collection Item Structure
JSON STRUCTUREOpenapi.Yaml Plugin Collection Structure
JSON STRUCTUREOpenapi.Yaml Pool Collection Structure
JSON STRUCTUREOpenapi.Yaml Pool Structure
JSON STRUCTUREOpenapi.Yaml Provider Collection Structure
JSON STRUCTUREOpenapi.Yaml Provider Structure
JSON STRUCTUREOpenapi.Yaml Relative Delta Structure
JSON STRUCTUREOpenapi.Yaml Resource Structure
JSON STRUCTUREOpenapi.Yaml Role Collection Structure
JSON STRUCTUREOpenapi.Yaml Role Structure
JSON STRUCTUREOpenapi.Yaml Schedule Interval Structure
JSON STRUCTUREOpenapi.Yaml Scheduler Status Structure
JSON STRUCTUREOpenapi.Yaml Set Dag Run Note Structure
JSON STRUCTUREOpenapi.Yaml Set Task Instance Note Structure
JSON STRUCTUREOpenapi.Yaml Sla Miss Structure
JSON STRUCTUREOpenapi.Yaml Tag Structure
JSON STRUCTUREOpenapi.Yaml Task Collection Structure
JSON STRUCTUREOpenapi.Yaml Task Instance Collection Structure
JSON STRUCTUREOpenapi.Yaml Task Instance Reference Structure
JSON STRUCTUREOpenapi.Yaml Task Instance Structure
JSON STRUCTUREOpenapi.Yaml Task Outlet Dataset Reference Structure
JSON STRUCTUREOpenapi.Yaml Task State Structure
JSON STRUCTUREOpenapi.Yaml Task Structure
JSON STRUCTUREOpenapi.Yaml Time Delta Structure
JSON STRUCTUREOpenapi.Yaml Timezone Structure
JSON STRUCTUREOpenapi.Yaml Trigger Rule Structure
JSON STRUCTUREOpenapi.Yaml Trigger Structure
JSON STRUCTUREOpenapi.Yaml Update Dag Run State Structure
JSON STRUCTUREOpenapi.Yaml Update Task Instance Structure
JSON STRUCTUREOpenapi.Yaml Update Task Instances State Structure
JSON STRUCTUREOpenapi.Yaml User Collection Item Structure
JSON STRUCTUREOpenapi.Yaml User Collection Structure
JSON STRUCTUREOpenapi.Yaml User Structure
JSON STRUCTUREOpenapi.Yaml Variable Collection Item Structure
JSON STRUCTUREOpenapi.Yaml Variable Collection Structure
JSON STRUCTUREOpenapi.Yaml Variable Structure
JSON STRUCTUREOpenapi.Yaml Version Info Structure
JSON STRUCTUREOpenapi.Yaml Weight Rule Structure
JSON STRUCTUREOpenapi.Yaml X Com Collection Item Structure
JSON STRUCTUREOpenapi.Yaml X Com Collection Structure
JSON STRUCTUREOpenapi.Yaml X Com Structure
JSON STRUCTUREScroll within the panel for all 84 ·
Examples 30
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.
Openapi.Yaml Action Example
EXAMPLEOpenapi.Yaml Color Example
EXAMPLEOpenapi.Yaml Config Example
EXAMPLEOpenapi.Yaml Dag Example
EXAMPLEOpenapi.Yaml Dag Run Example
EXAMPLEOpenapi.Yaml Dataset Example
EXAMPLEScroll within the panel for all 30 ·
Security Posture 3
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 6
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.
ETL Pipeline Orchestration
Schedule and manage extract, transform, load pipelines with dependency management and retry logic.
Machine Learning Workflows
Orchestrate ML training, validation, and deployment pipelines with data dependency tracking.
Data Warehouse Loading
Coordinate data ingestion from multiple sources into data warehouses like BigQuery, Redshift, and Snowflake.
Batch Report Generation
Schedule periodic batch reporting jobs with email notification on completion or failure.
Multi-Cloud Data Movement
Move data between AWS, GCP, and Azure using provider integrations with dependency control.
CI/CD Pipeline Orchestration
Trigger and monitor software deployment pipelines with upstream/downstream task dependencies.
Integrations 8
Pre-built integrations with other platforms tell you where this provider already fits in a stack.
Pre-built integrations with other platforms and tools.
Apache Spark
Native Spark submit and Livy operator integration for distributed data processing.
Google Cloud
Comprehensive GCP provider for BigQuery, Cloud Storage, Dataflow, Dataproc, and more.
Amazon Web Services
AWS provider for S3, Redshift, EMR, Glue, Lambda, and other services.
Microsoft Azure
Azure provider for Blob Storage, Data Factory, HDInsight, and Databricks.
dbt
dbt operator for running dbt transformations within Airflow pipelines.
Kubernetes
KubernetesPodOperator for running tasks in isolated Kubernetes pods.
Docker
DockerOperator for running tasks in Docker containers with isolated environments.
Apache Kafka
Kafka producers and consumers as Airflow tasks via the Kafka provider.
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Resources
Every other property we hold for Apache Airflow — 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
Documentation 1
Reference material describing how the API behaves
Agent Surfaces 4
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 19
Pagination, idempotency, versioning, errors, and events
Scroll within the panel for all 19 ·
Build 6
SDKs, sample code, and the tooling you integrate with
Access & Security 5
Authentication, authorization, and security posture
Learn 1
Tutorials, courses, talks, and written guidance
Operate 3
Status, limits, changes, and where to get help
Company 2
The organization behind the API
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