entra-agent-id

$npx mdskill add microsoft/skills/entra-agent-id

Create and manage OAuth2-capable AI agent identities via Microsoft Graph beta API.

  • Solves the need for secure, scoped identities for AI agents.
  • Depends on Microsoft Graph beta API and Entra SDK sidecar.
  • Uses Agent Identity Blueprints and BlueprintPrincipals to model agents.
  • Delivers agent identities as service principals with OAuth2 tokens.

SKILL.md

.github/skills/entra-agent-idView on GitHub ↗
---
name: entra-agent-id
description: |
  Microsoft Entra Agent ID (preview) for creating OAuth2-capable AI agent identities via Microsoft Graph beta API.
  Covers Agent Identity Blueprints, BlueprintPrincipals, Agent Identities, required permissions, sponsors, and Workload Identity Federation.
  Includes Microsoft Entra SDK for AgentID (containerized sidecar) for polyglot agent authentication (Docker/Kubernetes), 3P agent integration, autonomous and interactive agent patterns.
  Triggers: "agent identity", "agent id", "Agent Identity Blueprint", "BlueprintPrincipal", "entra agent", "agent identity provisioning", "Graph agent identity", "entra sidecar", "agent id sidecar", "auth sidecar", "3P agent", "third-party agent identity", "polyglot agent auth".
---

# Microsoft Entra Agent ID

Create and manage OAuth2-capable identities for AI agents using Microsoft Graph beta API.

> **Preview API** — All Agent Identity endpoints are under `/beta` only. Not available in `/v1.0`.

## Before You Start

Search `microsoft-docs` MCP for the latest Agent ID documentation:
- Query: "Microsoft Entra agent identity setup"
- Verify: API parameters match current preview behavior

## Conceptual Model

```
Agent Identity Blueprint (application)        ← one per agent type/project
  └── BlueprintPrincipal (service principal)   ← MUST be created explicitly
        ├── Agent Identity (SP): agent-1       ← one per agent instance
        ├── Agent Identity (SP): agent-2
        └── Agent Identity (SP): agent-3
```

## Prerequisites

### PowerShell (recommended for interactive setup)

```powershell
# Requires PowerShell 7+
Install-Module Microsoft.Graph.Beta.Applications -Scope CurrentUser -Force
```

### Python (for programmatic provisioning)

```bash
pip install azure-identity requests
```

### Required Entra Roles

One of: **Agent Identity Developer**, **Agent Identity Administrator**, or **Application Administrator**.

## Environment Variables

```bash
AZURE_TENANT_ID=<your-tenant-id>
AZURE_CLIENT_ID=<app-registration-client-id>
AZURE_CLIENT_SECRET=<app-registration-secret>
```

## Authentication

> **⚠️ `DefaultAzureCredential` is NOT supported.** Azure CLI tokens contain
> `Directory.AccessAsUser.All`, which Agent Identity APIs explicitly reject (403).
> You MUST use a dedicated app registration with `client_credentials` flow or
> connect via `Connect-MgGraph` with explicit delegated scopes.

### PowerShell (delegated permissions)

```powershell
Connect-MgGraph -Scopes @(
    "AgentIdentityBlueprint.Create",
    "AgentIdentityBlueprint.ReadWrite.All",
    "AgentIdentityBlueprintPrincipal.Create",
    "User.Read"
)
Set-MgRequestContext -ApiVersion beta

$currentUser = (Get-MgContext).Account
$userId = (Get-MgUser -UserId $currentUser).Id
```

### Python (application permissions)

```python
import os
import requests
from azure.identity import ClientSecretCredential

credential = ClientSecretCredential(
    tenant_id=os.environ["AZURE_TENANT_ID"],
    client_id=os.environ["AZURE_CLIENT_ID"],
    client_secret=os.environ["AZURE_CLIENT_SECRET"],
)
token = credential.get_token("https://graph.microsoft.com/.default")

GRAPH = "https://graph.microsoft.com/beta"
headers = {
    "Authorization": f"Bearer {token.token}",
    "Content-Type": "application/json",
    "OData-Version": "4.0",  # Required for all Agent Identity API calls
}
```

## Core Workflow

### Step 1: Create Agent Identity Blueprint

Sponsors are required and **must be User objects** — ServicePrincipals and Groups are rejected.

```python
import subprocess

# Get sponsor user ID (client_credentials has no user context, so use az CLI)
result = subprocess.run(
    ["az", "ad", "signed-in-user", "show", "--query", "id", "-o", "tsv"],
    capture_output=True, text=True, check=True,
)
user_id = result.stdout.strip()

blueprint_body = {
    "@odata.type": "Microsoft.Graph.AgentIdentityBlueprint",
    "displayName": "My Agent Blueprint",
    "[email protected]": [
        f"https://graph.microsoft.com/beta/users/{user_id}"
    ],
}
resp = requests.post(f"{GRAPH}/applications", headers=headers, json=blueprint_body)
resp.raise_for_status()

blueprint = resp.json()
app_id = blueprint["appId"]
blueprint_obj_id = blueprint["id"]
```

### Step 2: Create BlueprintPrincipal

> **This step is mandatory.** Creating a Blueprint does NOT auto-create its
> service principal. Without this, Agent Identity creation fails with:
> `400: The Agent Blueprint Principal for the Agent Blueprint does not exist.`

```python
sp_body = {
    "@odata.type": "Microsoft.Graph.AgentIdentityBlueprintPrincipal",
    "appId": app_id,
}
resp = requests.post(f"{GRAPH}/servicePrincipals", headers=headers, json=sp_body)
resp.raise_for_status()
```

If implementing idempotent scripts, check for and create the BlueprintPrincipal
even when the Blueprint already exists (a previous run may have created the Blueprint
but crashed before creating the SP).

### Step 3: Create Agent Identities

```python
agent_body = {
    "@odata.type": "Microsoft.Graph.AgentIdentity",
    "displayName": "my-agent-instance-1",
    "agentIdentityBlueprintId": app_id,
    "[email protected]": [
        f"https://graph.microsoft.com/beta/users/{user_id}"
    ],
}
resp = requests.post(f"{GRAPH}/servicePrincipals", headers=headers, json=agent_body)
resp.raise_for_status()
agent = resp.json()
```

## API Reference

| Operation | Method | Endpoint | OData Type |
|-----------|--------|----------|------------|
| Create Blueprint | `POST` | `/applications` | `Microsoft.Graph.AgentIdentityBlueprint` |
| Create BlueprintPrincipal | `POST` | `/servicePrincipals` | `Microsoft.Graph.AgentIdentityBlueprintPrincipal` |
| Create Agent Identity | `POST` | `/servicePrincipals` | `Microsoft.Graph.AgentIdentity` |
| List Agent Identities | `GET` | `/servicePrincipals?$filter=...` | — |
| Delete Agent Identity | `DELETE` | `/servicePrincipals/{id}` | — |
| Delete Blueprint | `DELETE` | `/applications/{id}` | — |

All endpoints use base URL: `https://graph.microsoft.com/beta`

## Required Permissions

| Permission | Purpose |
|-----------|---------|
| `Application.ReadWrite.All` | Blueprint CRUD (application objects) |
| `AgentIdentityBlueprint.Create` | Create new Blueprints |
| `AgentIdentityBlueprint.ReadWrite.All` | Read/update Blueprints |
| `AgentIdentityBlueprintPrincipal.Create` | Create BlueprintPrincipals |
| `AgentIdentity.Create.All` | Create Agent Identities |
| `AgentIdentity.ReadWrite.All` | Read/update Agent Identities |

There are **18 Agent Identity-specific** Graph application permissions. Discover all:
```bash
az ad sp show --id 00000003-0000-0000-c000-000000000000 \
  --query "appRoles[?contains(value, 'AgentIdentity')].{id:id, value:value}" -o json
```

Grant admin consent (required for application permissions):
```bash
az ad app permission admin-consent --id <client-id>
```

> Admin consent may fail with 404 if the service principal hasn't replicated. Retry with 10–40s backoff.

## Cleanup

```python
# Delete Agent Identity
requests.delete(f"{GRAPH}/servicePrincipals/{agent['id']}", headers=headers)

# Delete BlueprintPrincipal (get SP ID first)
sps = requests.get(
    f"{GRAPH}/servicePrincipals?$filter=appId eq '{app_id}'",
    headers=headers,
).json()
for sp in sps.get("value", []):
    requests.delete(f"{GRAPH}/servicePrincipals/{sp['id']}", headers=headers)

# Delete Blueprint
requests.delete(f"{GRAPH}/applications/{blueprint_obj_id}", headers=headers)
```

## Best Practices

1. **Always create BlueprintPrincipal after Blueprint** — not auto-created; implement idempotent checks on both
2. **Use User objects as sponsors** — ServicePrincipals and Groups are rejected
3. **Handle permission propagation delays** — after admin consent, wait 30–120s; retry with backoff on 403
4. **Include `OData-Version: 4.0` header** on every Graph request
5. **Use Workload Identity Federation for production auth** — for local dev, use a client secret on the Blueprint (see [references/oauth2-token-flow.md](references/oauth2-token-flow.md))
6. **Set `identifierUris` on Blueprint** before using OAuth2 scoping (`api://{app-id}`)
7. **Never use Azure CLI tokens** for API calls — they contain `Directory.AccessAsUser.All` which is hard-rejected
8. **Check for existing resources** before creating — implement idempotent provisioning

## References

| File | Contents |
|------|----------|
| [references/oauth2-token-flow.md](references/oauth2-token-flow.md) | Production (Managed Identity + WIF) and local dev (client secret) token flows |
| [references/known-limitations.md](references/known-limitations.md) | 29 known issues organized by category (from official preview known-issues page) |
| [references/sdk-sidecar.md](references/sdk-sidecar.md) | Microsoft Entra SDK for AgentID — endpoints, 3P agent patterns, Docker/K8s deployment, security |

### External Links

| Resource | URL |
|----------|-----|
| Official Setup Guide | https://learn.microsoft.com/en-us/entra/agent-id/identity-platform/agent-id-setup-instructions |
| AI-Guided Setup | https://learn.microsoft.com/en-us/entra/agent-id/identity-platform/agent-id-ai-guided-setup |
| Microsoft Entra SDK for AgentID — Overview | https://learn.microsoft.com/en-us/entra/msidweb/agent-id-sdk/overview |
| Microsoft Entra SDK for AgentID — Endpoints | https://learn.microsoft.com/en-us/entra/msidweb/agent-id-sdk/endpoints |

More from microsoft/skills

SkillDescription
agent-framework-azure-ai-pyBuild Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code interpreter, file search, web search), integrating MCP servers, managing conversation threads, or implementing streaming responses. Covers function tools, structured outputs, and multi-tool agents.
airunway-aks-setupSet up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: \"setup AI Runway\", \"onboard AKS cluster\", \"install AI Runway\", \"airunway setup\", \"deploy model to AKS\", \"GPU inference on AKS\", \"KAITO setup on AKS\", \"run LLM on AKS\", \"vLLM on AKS\", \"set up model serving on AKS\", \"AI Runway controller\".
appinsights-instrumentationGuidance for instrumenting webapps with Azure Application Insights. Provides telemetry patterns, SDK setup, and configuration references. WHEN: how to instrument app, App Insights SDK, telemetry patterns, what is App Insights, Application Insights guidance, instrumentation examples, APM best practices.
applicationinsights-web-tsInstrument browser/web apps with the Application Insights JavaScript SDK (@microsoft/applicationinsights-web). Use for Real User Monitoring (RUM) — page views, clicks, AJAX/fetch dependencies, exceptions, custom events, and browser-side GenAI agent traces correlated to backend OpenTelemetry traces. Covers SDK Loader Script and npm setup, framework extensions (React, React Native, Angular), Click Analytics, telemetry initializers, and OTel GenAI semantic conventions for agent/tool/model spans emitted from the browser.
azure-aiUse for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.
azure-ai-agents-persistent-dotnet|
azure-ai-agents-persistent-java|
azure-ai-anomalydetector-javaBuild anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate/multivariate anomaly detection, time-series analysis, or AI-powered monitoring.
azure-ai-contentsafety-javaBuild content moderation applications with Azure AI Content Safety SDK for Java. Use when implementing text/image analysis, blocklist management, or harm detection for hate, violence, sexual content, and self-harm.
azure-ai-contentsafety-py|