Apache APIs for AI Agents
Developer ToolsCi CdMonitoring ObservabilityOfficial Vendor Specsbasic, openIdConnect, httpNo authAgent Ready
For Agents
APIs2 in catalogue
Endpoints99 indexed
Authbasic, openIdConnect, http / No auth
ProvenanceOfficial OpenAPI specs
An agent can trigger and monitor Apache Airflow DAG runs, inspect task instances, and manage Airflow connections and variables, and can create queues, enqueue and dequeue messages, and acknowledge processed work on a self-hosted Qakka deployment.
Apache's APIs here cover two ends of self-hosted data infrastructure: Airflow orchestrates and schedules pipelines while Qakka moves individual messages between services. Both are open source under the Apache 2.0 license and run on infrastructure you control, so an agent operates your own deployment rather than a hosted vendor service.
Use for: Operating self-hosted Apache infrastructure from automation: triggering and inspecting Airflow DAG runs and task instances, managing Airflow connections and variables, and creating queues plus enqueuing, dequeuing, and acknowledging Qakka messages.
Not supported: DAG authoring, code deployment, web UI, pub-sub topics, stream processing, exactly-once delivery
Credentials: No; the two APIs use independent auth models set per deployment (Airflow supports HTTP basic, Google OpenID Connect, or Kerberos, while Qakka declares no security scheme and relies on a network control or reverse proxy), so each is configured with its own credential.
All 2 Apache OpenAPI specs are vendor-official and indexed by Jentic, kept validated and agent-ready.
The Apache Software Foundation stewards open-source infrastructure projects, several of which expose HTTP APIs for programmatic control. On Jentic, Apache is represented by two of these: the Airflow stable REST API for workflow orchestration, and Qakka, the lightweight queue system from the Apache Usergrid project. Airflow lets external systems trigger and inspect DAG runs and manage connections, variables, datasets, and pools without the web UI. Qakka provides a small queue surface for service-to-service messaging where a full broker would be excessive. Both are self-hosted: the deployment host, auth backend, and base URL are set per installation rather than by a shared vendor endpoint.
Apache API Catalog
2 APIs across 1 product group.
Developer Tools2
Airflow API (Stable)Trigger DAG runs, inspect task instances, and manage Airflow connections, variables, and datasets across an Apache Airflow deployment.~89 endpointsQakkaCreate and configure queues, send and receive messages, and acknowledge processed messages on a self-hosted Qakka deployment.~10 endpoints
Which Apache API should I use?
| I want to... | Use | Why |
|---|---|---|
| Schedule and monitor a multi-step data or ETL pipeline | Airflow API (Stable) | Airflow orchestrates DAGs, tracks per-task state, and manages the connections and variables those pipelines depend on. |
| Hand off individual jobs between services with a lightweight queue | Qakka | Qakka offers a small enqueue, dequeue, and acknowledge surface for at-least-once messaging without a full broker like Kafka. |
Install Jentic One Beta
Connect the Apache APIs to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Apache APIs, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.
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Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fapache.org" | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fapache.org" | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
Once connected, ask your agent something like: “orchestrate and queue work across self-hosted Apache infrastructure”.
What AI Agents Can Do with Apache
Each workflow spans multiple Apache APIs. Jentic routes each operation to the right API automatically.
Queue-backed pipeline with orchestrated workers
Use Qakka as the transport that carries jobs between services and Airflow to schedule the producers and consumers that drain those queues. An agent enqueues work items into Qakka, then triggers an Airflow DAG whose tasks pull and process the queued messages, giving a decoupled pipeline where Airflow owns scheduling and state while Qakka owns handoff.
Example prompt:
POST job payloads to /queues/etl-jobs/messages on Qakka, then trigger the consumer DAG via POST /dags/etl_worker/dagRuns on Airflow and poll the DAG run for completion
APIs used
Airflow API (Stable) + Qakka
Health and state dashboard across orchestration and queueing
Build a single operations view that reports both pipeline health and messaging health for a self-hosted Apache stack. The agent aggregates Airflow DAG and task run state and checks Qakka reachability and queue presence, surfacing failures from either layer in one digest.
Example prompt:
GET /dags then /dags/{dag_id}/dagRuns on Airflow to count failed runs, and GET /status plus /queues on Qakka to confirm queues exist, then post a combined health summary
APIs used
Airflow API (Stable) + Qakka
Why Jentic?
What agents get from Jentic-routed access to this vendor.
Setup
Wiring these Apache APIs by hand means pointing at each of your own deployments, picking Airflow's auth backend among basic, OpenID Connect, and Kerberos, handling Qakka's deployment-level protection, and mapping the run, task, metadata, and queue routes yourself. Through Jentic you install once, import Airflow and Qakka from the Jentic API Directory, store each credential once, and your agent calls them.
Permission scoping
Both APIs put the target in the URL path, Airflow with /dags/{dag_id} and Qakka with /queues/{queueName}, so your own rules can pin the agent to a single DAG or a single queue. You also choose which operations each API exposes, so destructive ones like clearing task instances or deleting queues are available only if you add them.
Credential isolation
Each deployment credential, whether an Airflow basic or OIDC secret or a Qakka proxy token, is stored once, encrypted, by your own Jentic One instance and injected at execution time. It never enters the agent's prompt, logs, or context.
Intent-based discovery
Agents search Jentic by intent such as 'trigger an Airflow DAG' or 'send a message to a queue', and Jentic returns the matching Apache operation with its input schema so the agent calls the right endpoint without browsing the reference docs.
FAQs
Specific to using Apache APIs through Jentic.
Which Apache APIs are available through Jentic?
Two: the Apache Airflow stable REST API for workflow orchestration, and Qakka, the lightweight queue system from the Apache Usergrid project. Airflow covers DAGs, runs, task instances, connections, variables, datasets, and pools; Qakka covers queue lifecycle, message enqueue and dequeue, and acknowledgement.
Do Airflow and Qakka share one set of credentials?
No. They are separate projects with independent auth. Airflow supports HTTP basic, Google OpenID Connect, or Kerberos depending on the deployment's configuration, while Qakka declares no security scheme and is protected by whatever network control or reverse proxy sits in front of it. Each is configured with its own credential.
Are these Apache APIs hosted by Apache or self-hosted?
Self-hosted. Both Airflow and Qakka run on infrastructure you operate, so the base URL, host, and auth backend are set by your deployment rather than by a shared Apache endpoint. Through Jentic your agent operates your own running instances.
When should an agent use Airflow versus Qakka?
Use Airflow to schedule and monitor multi-step pipelines where each task has state you want to track and recover. Use Qakka to move individual messages between services when a lightweight at-least-once queue is enough and a full broker would be excessive. They also work together, with Airflow scheduling workers that drain Qakka queues.
Are these APIs free to use?
Both Airflow and Qakka are open source under the Apache 2.0 license, so the APIs themselves are free. The cost is the infrastructure that runs them, or a managed Airflow offering such as Astronomer or AWS MWAA if you choose one.
Can I limit what my agent is allowed to do across these APIs?
Yes. Because you run Jentic One yourself, your own rules decide which operations and credentials the agent may use for each API. Both APIs put the target in the URL path, so a rule can pin the agent to a single DAG on Airflow or a single queue on Qakka, and you choose which operations are exposed so destructive ones like clearing task instances or deleting queues stay off unless you add them.
If you need a different Developer Tools vendor
All 3 are in the Jentic catalogue with the same one-credential, intent-search pattern.
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