Azure OpenAI Service
Azure OpenAI Service (part of Microsoft Foundry Models) provides REST API access to OpenAI models including GPT, o-series reasoning models, DALL-E, Whisper, and embedding models, hosted within Microsoft Azure with enterprise security, regional availability, private networking, content filtering, and Microsoft Entra ID integration. The data-plane REST API exposes endpoints for chat completions, completions, embeddings, image generation, audio transcription/translation, fine-tuning, and the Responses API, while the control-plane API manages Azure OpenAI resources and deployments.
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 Azure OpenAI Service the way a machine reads it — 17 machine-readable artifacts across 8 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 — Azure OpenAI Service scores 41.7/100 (thin), with a separate agent-readiness read of 47/100 (agent ready). 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 Azure OpenAI Service
Each block below is one kind of artifact we hold for Azure OpenAI Service. 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 8
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.
Azure OpenAI Inference REST API
Data-plane REST API for running inference against deployed Azure OpenAI models, including chat completions, completions, embeddings, image generation, and audio transcription/tr...
Azure OpenAI Responses API
Stateful, agent-friendly API for building multi-turn AI experiences with tool use, file inputs, and conversation state managed on the service side.
Azure OpenAI Control Plane API
Azure Resource Manager (ARM) REST API for creating and managing Azure OpenAI accounts, model deployments, network rules, and other resource configuration.
Azure OpenAI Service Audio API
Audio transcription and translation (Whisper)
Azure OpenAI Service Chat Completions API
Chat-formatted text generation
Azure OpenAI Service Completions API
Plain text completions
Azure OpenAI Service Embeddings API
Vector embeddings
Azure OpenAI Service Images API
Image generation (DALL-E)
Scroll within the panel for all 8 ·
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).
Azure OpenAI Inference REST 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.
Azure OpenAI Service GraphQL API
Azure OpenAI Service provides REST API access to OpenAI models (GPT-4, GPT-3.5, DALL-E, Whisper, Embeddings) with enterprise SLAs, private networking, and Azure identity. The AP...
GRAPHQLEvent Specifications 1
Not every API is request/response. AsyncAPI describes the event-driven and streaming side — the webhooks and channels — so the asynchronous half of the interface is documented the same way the synchronous half is.
AsyncAPI definitions for this provider's event-driven and streaming APIs.
Azure OpenAI Service - Streaming and Realtime APIs
AsyncAPI 2.6 description of the asynchronous and streaming surfaces of the Azure OpenAI Service (part of Microsoft Foundry Models): * The **Realtime API** over a WebSocket conne...
ASYNCAPISpectral Rules 1
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.
Azure OpenAI Service API Rules
SPECTRALSecurity 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.
Scopes 1
OAuth scopes are the vocabulary of least-privilege access. Profiling them shows exactly what an integration — or an agent acting on a user's behalf — is allowed to do.
OAuth scopes governing access to this provider's APIs.
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.
Resources
Every other property we hold for Azure OpenAI Service — 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 2
Portal, sign-up, and the first successful call
Documentation 3
Reference material describing how the API behaves
Agent Surfaces 2
MCP servers, agent skills, and machine-readable catalogs
Build 1
SDKs, sample code, and the tooling you integrate with
Access & Security 4
Authentication, authorization, and security posture
Commercial 1
Pricing, plans, and the legal terms of use
Company 2
The organization behind the API
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