Microsoft Azure AI Foundry
Microsoft Azure AI Foundry (formerly Azure AI Studio) is an end-to-end platform for building, optimizing, evaluating, and governing AI applications and agents at scale. It provides access to Foundry Models (including Azure OpenAI and open-source models), the Foundry Agent Service, content safety, observability, and responsible AI tooling. The Foundry REST APIs and Azure SDKs use Microsoft Entra ID OAuth 2.0 bearer tokens or API keys for authentication.
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 Microsoft Azure AI Foundry the way a machine reads it — 12 machine-readable artifacts across 6 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 — Microsoft Azure AI Foundry scores 30.0/100 (thin), with a separate agent-readiness read of 41/100 (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 Microsoft Azure AI Foundry
Each block below is one kind of artifact we hold for Microsoft Azure AI Foundry. 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 6
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 AI Foundry REST API
REST API for managing Foundry projects, hubs, model deployments, agents, threads, runs, and evaluations. Authentication uses Microsoft Entra ID OAuth 2.0 bearer tokens (or API k...
Microsoft Azure AI Foundry Chat Completions API
Chat-formatted text generation
Microsoft Azure AI Foundry Completions API
Plain text completions
Microsoft Azure AI Foundry Embeddings API
Vector embeddings for text
Microsoft Azure AI Foundry Images API
Image generation
Microsoft Azure AI Foundry Models API
Model and deployment metadata
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 AI Foundry Model Inference REST API
OPEN COLLECTIONSecurity 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 Microsoft Azure AI Foundry — 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 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
← All providers · Data indexed from github.com/api-evangelist/azure-ai-foundry · machine-readable index on apis.io