Oracle Fusion AI Agent REST API

Scope note — three closely related pages, one direction each. "AI agent" and "REST" appear together in three different Fusion contexts. This page covers only one of them. Keep the direction of the call straight:

This page — the inbound REST API (app → agent). The REST endpoint that external applications call to invoke a Fusion agent. The mechanics of the request, the polling and SSE response patterns, and the async lifecycle.
The agent calling out (agent → third-party API). When an agent uses an external REST call as a tool to reach a third-party service, that is a different capability — see AI Agent Studio REST tools.
The broader external-access model. The wider picture of external invocation — identity, tokens, roles, async patterns and audit across every entry point — is covered on AI agent external access. This page is the REST-specific slice of that model.

Agent-to-agent interoperability (one agent invoking another) is a separate protocol again — see Oracle AI Agent2Agent (A2A).

What the Oracle AI Agent REST API Does

Agents built and deployed in Oracle AI Agent Studio normally run inside Fusion — triggered from a workflow, a page, or a supported channel. The REST API opens a further door: an application outside Fusion can send a request that invokes the agent, receive the agent's response, and act on it. This turns a Fusion agent into a service that your own systems can consume.

Typical consumers of this pattern include a customer-facing portal that wants an agent to answer a question, a middleware or integration flow that orchestrates an agent as one step in a larger process, a custom internal application that surfaces an agent's recommendation, or an automation that needs an agent to perform a task and report back. In every case the external app is the caller, and the Fusion agent is the callee.

Because an agent can reason over knowledge sources, invoke tools and take actions within Fusion, an inbound REST call is not a simple read. It can trigger real work under the identity that made the call. That is why identity, role-based access, and — where an agent's tools require it — human-approval gates matter as much as the request format itself. Availability: Generally available in release 26A; confirm the current enablement steps for your environment with Oracle.

What this page does not claim. Oracle documents the capability as a REST API that supports polling or SSE, generally available in 26A. It does not publish, and this page does not invent, specific endpoint paths, request or response payload schemas, header names, or version strings. Treat the official Oracle documentation as the source of truth for exact request formats, and design your tests to read those from the live API rather than from any assumed contract.

Invocation Patterns: Polling vs SSE

An agent invocation is not instantaneous — the agent reasons, may call tools, and may wait on an approval before it produces a result. Oracle therefore offers two ways for the caller to receive that result. Both are generally available in 26A; the right choice depends on how your application consumes the response.

Polling

The caller submits the invocation, then asks again on an interval until the agent's response is ready. Simple to implement, resilient across proxies and gateways that buffer or close long-lived connections, and a natural fit for middleware and batch-style integrations.

Best for: server-to-server flows, integrations behind API gateways, jobs that can wait.
Design cost: choosing a poll interval and a give-up timeout; avoiding tight loops.
Test focus: completion is eventually returned, interim status is correct, and a slow agent does not cause a false timeout.

SSE (Server-Sent Events)

The caller opens a streamed connection and Oracle pushes the response as it becomes available. Suited to interactive experiences where a user watches an answer arrive, and to any client that benefits from incremental output rather than a single final block.

Best for: chat-style UIs, human-facing apps, low-latency perceived response.
Design cost: the client and any intermediary must support and not buffer the stream; reconnection handling.
Test focus: the stream opens, events arrive in order, the stream closes cleanly, and a dropped connection is handled.

A robust integration usually settles on one pattern per consumer, but a test suite should exercise both — because the same agent reached two ways must return a consistent result, and each transport fails in its own way. Do not assume the two paths are interchangeable at the assertion level; verify each independently.

Authentication & Identity

An inbound agent call is an authenticated Fusion request. The external application must present a valid identity, and Fusion resolves that identity to a user or client before the agent runs. The agent then operates within the permissions of that identity — it does not gain elevated access simply because it was reached over REST.

This is the point most external-invocation designs get wrong. Because the caller is outside Fusion, teams sometimes treat the REST endpoint as a "system" door and wire a single shared credential behind it. That collapses accountability: every agent action then appears to come from one identity, and you lose the ability to answer "who asked the agent to do this?" The identity, token and audit details of that model are covered in depth on AI agent external access; on this page the point is narrower — the REST call carries an identity, and that identity determines what the agent may do.

For testing, treat authentication as a first-class scenario, not a precondition you set up once and forget. A call with no credential, an expired credential, a valid credential for the wrong user, and a valid credential for an authorised user should each produce a distinct, predictable outcome. Confirm the exact authentication and token mechanics for your environment against Oracle's documentation rather than assuming a scheme.

Availability note. The inbound REST API is generally available in release 26A. Related Agent Studio integrations — external REST tools and MCP tools — were also enhanced or introduced in 26A, and agent-to-agent (A2A) invocation is a later addition. When you read "26A" here it refers specifically to external applications invoking agents via REST with polling or SSE.

Role-Based Access

Once identity is established, Fusion's role-based access model governs what the invocation can actually reach. An agent invoked over REST runs within the roles and privileges of the calling identity — the same security framework that governs any Fusion user. An agent cannot read data or perform an action the calling identity is not entitled to.

This has two practical consequences for anyone exposing an agent over REST. First, the answer an agent returns can legitimately differ by caller, because two identities may see different data. Second, the set of callers permitted to invoke a given agent is itself an access-control decision that must be provisioned and reviewed, not left implicit. Under-scoping frustrates legitimate integrations; over-scoping hands an external door more reach than intended.

Because agent invocation can span data access, tool use and transactional actions, role design here overlaps with segregation-of-duties concerns — an external caller should not be able to reach, through an agent, a combination of actions that policy forbids a single user to perform directly. SyntraFlow's Oracle Fusion Segregation of Duties capability can complement agent access review by helping organizations assess whether the roles behind agent-invoking identities introduce conflicting privileges; treat that as a complementary control to confirm during assessment, not an automatic guarantee.

Access dimension	Who / what it governs	What to verify
Invocation right	Which identities may call the agent at all	Unauthorised identity is refused before the agent runs
Data scope	What business data the calling identity can see	Agent response reflects the caller's data entitlement, not more
Action scope	What transactions the agent may perform for that identity	Actions beyond the caller's privileges are blocked
Tool exposure	Which agent tools are reachable via the call	Sensitive tools require the expected privilege / approval
Approval gates	Where a human must confirm before an action executes	Gate fires and the action waits — see human-approval page
SoD overlap	Whether combined reachable actions breach a policy	No forbidden combination is reachable through one caller

Asynchronous Behaviour

Agent invocation is inherently asynchronous. The agent may reason for several seconds, call one or more tools, wait on a downstream service, or pause on a human-approval gate before it can return. Both the polling and SSE patterns exist precisely because a single synchronous request/response is a poor fit for that reality.

A caller therefore has to reason about state over time, not just a single reply. An invocation is submitted; it is in progress; it may be waiting on an approval; it completes with a result; or it ends in an error. A well-behaved client observes that lifecycle rather than assuming the first response is the final one. Where a human approval is required before an agent takes an action, the invocation can legitimately remain unresolved until that approval is granted — the deep treatment of those gates lives on AI agent human approval.

The testing implication is that timing is a test dimension, not an environmental nuisance. A suite should cover a fast completion, a slow completion that still succeeds, a completion that waits on an approval before finishing, and a caller that abandons the wait. Each has a correct behaviour, and each is a distinct assertion. Confirm the exact status semantics your Fusion environment reports against Oracle's documentation rather than inferring them from a single happy-path run.

Invocation lifecycle

External app calls REST → Identity & role check → Agent reasons / calls tools → Approval gate? → Result via polling or SSE → Caller consumes response

Submit: the external application authenticates and sends the invocation.
In progress: the agent works; the caller polls or receives streamed events.
Waiting: where a tool requires human approval, the invocation can pause until the gate is resolved.
Complete: the final response is returned and the caller acts on it.
Error: authentication, authorisation, timeout, or agent-side failures each surface distinctly.

Error Handling

Because an inbound agent call crosses a trust boundary and runs real work, its failure modes are broader than a typical read API. A caller must distinguish an authentication failure from an authorisation refusal, a transient timeout from a permanent agent error, and an agent that declined an action from one that could not perform it. Collapsing all of these into a single "it failed" makes integrations brittle and hides genuine control failures.

Good error handling on the caller side means deciding, per failure class, whether to retry, escalate, or surface the error to a user — and doing so without retrying an action that may have partially executed. On the SSE path, a dropped stream is its own case: the caller must know whether the underlying invocation continued server-side. Treat every row below as a test case with an expected, asserted outcome rather than a hypothetical.

Failure class	Example trigger	Expected caller behaviour
Unauthenticated	Missing or expired credential	Reject before invocation; do not retry blindly
Unauthorised	Valid identity, insufficient role	Refuse cleanly; surface as access error, not agent error
Timeout	Agent slower than the caller's wait window	Distinguish from failure; avoid duplicate side effects on retry
Stream drop (SSE)	Connection closes mid-response	Determine whether the invocation continued; reconcile
Awaiting approval	Action needs a human gate	Treat as pending, not failed; wait or notify
Agent-side error	Tool call fails or agent cannot complete	Surface the reason; do not present a partial result as final
Malformed request	Bad input from the calling application	Fail fast with a clear cause; log for the integration owner

Security Considerations

Exposing an agent over REST widens its attack surface: the caller is now outside Fusion, and the agent can reason, invoke tools, and act. Security here is not one control but the sum of identity, role scope, tool exposure, approval gates, and audit — each of which must hold under an external caller, not just an internal one.

The specific risks worth naming for an inbound REST agent, and the control that addresses each:

Risk	Why it matters over REST	Primary control
Shared / over-broad credential	One identity behind the door erases accountability	Per-caller identity; least-privilege roles
Privilege escalation via agent	Agent reaches actions the caller should not	Agent runs within the caller's role scope
Unapproved action execution	A tool takes an action with no human check	Human-approval gate before the action
Data leakage in response	Agent returns more than the caller may see	Response bound to caller's data entitlement
Prompt / input abuse	Hostile input steers the agent's behaviour	Input validation; constrained instructions and tools
SoD conflict through an agent	Reachable actions combine into a forbidden pair	SoD review of agent-invoking roles
Weak audit of external calls	"Who invoked what" is unanswerable after the fact	Per-invocation audit tied to caller identity

Several of these controls are shared with the broader external-invocation model and the human-approval design; this page names them as they apply to the REST entry point specifically. For the enterprise-wide identity, token and audit framework, defer to AI agent external access.

Oracle AI Agent REST API Test Matrix

A structured set of test areas for validating an inbound agent REST integration — covering both transports, identity and role scope, the async lifecycle, error handling, and security. Test IDs use the AI-API prefix. Adapt each to the exact request format your Oracle documentation specifies; do not hard-code an assumed contract.

ID	Test area	Scenario	Expected result	Pri
AI-API-001	Polling — happy path	Authorised caller invokes, polls to completion	Final response returned; status progresses correctly	H
AI-API-002	SSE — happy path	Authorised caller opens stream, receives events	Events arrive in order; stream closes cleanly	H
AI-API-003	Cross-transport parity	Same input via polling and via SSE	Consistent agent result across both paths	H
AI-API-004	No credential	Call with missing authentication	Rejected before invocation; agent does not run	H
AI-API-005	Expired credential	Call with an expired token	Authentication failure; clear error class	H
AI-API-006	Authorised identity	Valid identity with invocation right	Agent runs within that identity's scope	H
AI-API-007	Unauthorised identity	Valid identity without invocation right	Refused as access error, not agent error	H
AI-API-008	Data-scope boundary	Two identities with different data entitlement	Each response reflects only that caller's data	H
AI-API-009	Action-scope boundary	Caller lacks privilege for an agent action	Action blocked; no side effect	H
AI-API-010	Approval gate fires	Agent tool requires human approval	Invocation pends; action waits for approval	H
AI-API-011	Approval granted	Human approves the pending action	Invocation resumes and completes	M
AI-API-012	Slow completion	Agent runs longer than a naive timeout	Completion still returned; no false failure	M
AI-API-013	Poll timeout / abandon	Caller stops polling before completion	Clean give-up; no duplicate side effect on retry	M
AI-API-014	SSE stream drop	Connection closes mid-response	Caller reconciles server-side state correctly	M
AI-API-015	Malformed request	Bad input from the calling application	Fails fast with a clear, logged cause	M
AI-API-016	Agent-side error	A tool call fails during the run	Error surfaced; no partial result presented as final	M
AI-API-017	Data-leakage check	Attempt to elicit out-of-scope data	Response stays within caller entitlement	H
AI-API-018	Input-abuse resistance	Hostile input tries to steer behaviour	Agent stays within constrained instructions / tools	M
AI-API-019	Audit trail	Any invocation, success or failure	Caller identity and outcome recorded	M
AI-API-020	Regression after update	Re-run pack after a Fusion quarterly update	Behaviour unchanged, or changes are caught	H

Risk Table for Inbound Agent REST Integrations

The failure modes that carry real consequence when an agent is exposed over REST, with a likelihood and impact read and the testing response that catches each. Use it to prioritise the test matrix above against your own exposure.

Risk	Example	Likelihood	Impact	Testing response
Over-privileged caller	Agent acts beyond the caller's real entitlement	Medium	High	Action-scope boundary tests per identity
Data leakage	Response includes data the caller cannot see	Medium	High	Data-scope and leakage-elicitation tests
Bypassed approval	A gated action executes with no human check	Low	High	Approval-gate fires / grant tests
Duplicate side effect	Timeout retry runs an action twice	Medium	Medium	Timeout / abandon and idempotency tests
Transport divergence	Polling and SSE return different results	Low	Medium	Cross-transport parity tests
Silent update drift	A quarterly update changes API behaviour	Medium	Medium	Release-scoped regression on the API pack
Input abuse	Hostile input redirects agent behaviour	Medium	Medium	Input-abuse and constraint tests
Weak audit	External invocation not attributable later	Low	Medium	Per-invocation audit assertions
SoD conflict via agent	One caller reaches a forbidden action pair	Low	High	SoD review of agent-invoking roles

Release & Availability

Inbound REST invocation of Fusion AI agents — external applications calling an agent, with responses delivered by polling or SSE — is generally available in release 26A. Oracle AI Agent Studio itself has been generally available since 25C, and several related integrations arrived alongside the REST API in the same 26A wave, with agent-to-agent (A2A) invocation following later.

Because Fusion updates quarterly, treat the API's behaviour as something to re-verify each release rather than assume is fixed. A change to authentication handling, status semantics, or an agent's own configuration can alter how your integration behaves without any change on your side. That is exactly why the regression row in the test matrix exists. Where this page describes a capability, it is labelled with its availability; where a detail depends on your environment, confirm the current behaviour with Oracle rather than inferring it.

Capability	Availability
Oracle AI Agent Studio	Generally available (release 25C)
Inbound REST API to invoke agents (polling or SSE)	Generally available (release 26A)
External REST tools (agent calling out) & MCP tools	Introduced / enhanced (release 26A)
Agent-to-agent (A2A) invocation	Announced for a later release — confirm current availability with Oracle

How SyntraFlow Helps Validate Agent REST Integrations

SyntraFlow is a testing platform for Oracle Fusion. For an inbound agent REST API, its value is in exercising both transports, the identity and role boundaries, and the async lifecycle, then keeping that coverage current across quarterly updates. The points below are framed as configurable capabilities, confirmed at assessment — not automatic guarantees.

Both transports

SyntraFlow can be configured to exercise the polling and SSE paths and assert a consistent agent result across them.

Identity & role boundaries

Test packs can be set up to invoke the same agent under different identities and assert data and action scope hold.

Async lifecycle

SyntraFlow helps organizations assess slow completions, approval-gated pauses, and abandoned waits as distinct cases.

Negative & error cases

Coverage can be configured for missing and expired credentials, malformed requests, timeouts, and stream drops.

Release-aware regression

SyntraFlow can connect release intelligence with test planning to re-run the API pack that a quarterly update affects.

Evidence for audit

Runs can be configured to retain per-invocation results and caller identity as evidence for review and sign-off.

A note on scope. The list above describes how SyntraFlow can be configured to support validation of an Oracle AI agent REST integration. Exact coverage for your agents, identities and environment is confirmed during assessment rather than assumed here. Where role and privilege combinations behind agent-invoking identities need review, this pairs naturally with SyntraFlow's Oracle Fusion Segregation of Duties capability as a complementary control.

Related Oracle AI Pages

The inbound REST API sits within a cluster of closely related capabilities. Go to the right page for the direction you mean:

Oracle AI Agent Studio ⭐

The parent — build and deploy Fusion agents.

AI Agent External Access →

The broader external-invocation model.

AI Agent Studio REST Tools →

The agent calling out to a third-party API.

AI Agent Human Approval →

Approval gates before an agent acts.

Oracle AI Agent2Agent (A2A) →

Agent-to-agent interoperability.

Oracle AI Hub →

The whole Oracle AI vertical.

Official Oracle References

Verify request formats and current behaviour against Oracle's own documentation. The sources relevant to this page:

Last reviewed: 19 July 2026. Availability and behaviour described here reflect Oracle's 26A readiness content; confirm current details for your environment with Oracle.

Frequently Asked Questions

What is the Oracle AI agent REST API?

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It is the REST API that lets an external application invoke a Fusion AI agent — your software sends a request, the agent runs inside Fusion, and the response comes back either by polling or by SSE (Server-Sent Events). It is generally available in release 26A. This page covers that inbound direction: an app calling in to invoke an agent.

How is this different from AI Agent Studio REST tools?

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The direction of the call is opposite. This page is the inbound API — an external app invokes a Fusion agent. AI Agent Studio REST tools is the outbound case — a Fusion agent calls out to a third-party REST API as one of its tools. Same technology family, different party initiating the call.

How does this differ from AI agent external access?

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AI agent external access covers the broad external-invocation model — identity, tokens, role-based access, async patterns and audit across every entry point. This page is the REST-specific slice of that: the endpoint mechanics, the polling and SSE patterns, and the tests around them. For the enterprise-wide identity and audit framework, use the external-access page.

Should I use polling or SSE?

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Polling suits server-to-server flows, integrations behind API gateways, and jobs that can wait — it is simple and resilient. SSE suits interactive, human-facing experiences where a user watches the response arrive. Both are generally available in 26A. Whichever you choose in production, test both paths, because the same agent reached two ways should return a consistent result.

Does an agent invoked over REST bypass Fusion security?

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No. The call is authenticated, and the agent runs within the roles and privileges of the calling identity — it cannot read data or take an action the caller is not entitled to. The common mistake is wiring a single shared, over-broad credential behind the endpoint, which erases accountability. Use per-caller identity and least-privilege roles, and confirm the token mechanics with Oracle.

What happens when an agent action needs human approval?

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The invocation can pause until the gate is resolved — a pending state, not a failure. A well-behaved caller treats that as "awaiting approval" and waits or notifies, rather than retrying. The deep treatment of approval gates lives on the AI agent human approval page; here it is one state in the async lifecycle your tests should cover.

What should an agent REST API test suite cover?

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Both transports and their parity; authentication and authorisation cases; data and action scope per identity; the async lifecycle including slow completions and approval-gated pauses; error handling for timeouts, stream drops, malformed requests and agent-side errors; data-leakage and input-abuse checks; audit; and release-scoped regression. The test matrix on this page lays out a representative set with an AI-API prefix.

Can SyntraFlow test the Oracle AI agent REST API?

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SyntraFlow can be configured to exercise both transports, invoke the same agent under different identities to check role and data scope, cover negative and async cases, and re-run the pack when a quarterly update affects it. Exact coverage for your agents and environment is confirmed at assessment rather than assumed. Where agent-invoking roles need review, it pairs with SyntraFlow's Segregation of Duties capability as a complementary control.