Azure API Center Management SDK for Python

SkillCloud & infra

Lets your agent manage your organization's API inventory, metadata, and governance in Azure API Center.

Available today. Use it from your connected AI after setup.

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Then ask your AI: use the Azure API Center Management SDK for Python skill

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What this skill tells your AI

The instructions your AI receives, as published by benjaminastera/antigravity-awesome-skills in skills/azure-mgmt-apicenter-py/SKILL.md and read by ahel’s review.

Manage API inventory, metadata, and governance in Azure API Center.

Installation

pip install azure-mgmt-apicenter
pip install azure-identity

Environment Variables

AZURE_SUBSCRIPTION_ID=your-subscription-id

Authentication

from azure.identity import DefaultAzureCredential
from azure.mgmt.apicenter import ApiCenterMgmtClient
import os

client = ApiCenterMgmtClient(
    credential=DefaultAzureCredential(),
    subscription_id=os.environ["AZURE_SUBSCRIPTION_ID"]
)

Create API Center

from azure.mgmt.apicenter.models import Service

api_center = client.services.create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-api-center",
    resource=Service(
        location="eastus",
        tags={"environment": "production"}
    )
)

print(f"Created API Center: {api_center.name}")

List API Centers

api_centers = client.services.list_by_subscription()

for api_center in api_centers:
    print(f"{api_center.name} - {api_center.location}")

Register an API

from azure.mgmt.apicenter.models import Api, ApiKind, LifecycleStage

api = client.apis.create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-api-center",
    workspace_name="default",
    api_name="my-api",
    resource=Api(
        title="My API",
        description="A sample API for demonstration",
        kind=ApiKind.REST,
        lifecycle_stage=LifecycleStage.PRODUCTION,
        terms_of_service={"url": "https://example.com/terms"},
        contacts=[{"name": "API Team", "email": "api-team@example.com"}]
    )
)

print(f"Registered API: {api.title}")

Create API Version

from azure.mgmt.apicenter.models import ApiVersion, LifecycleStage

version = client.api_versions.create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-api-center",
    workspace_name="default",
    api_name="my-api",
    version_name="v1",
    resource=ApiVersion(
        title="Version 1.0",
        lifecycle_stage=LifecycleStage.PRODUCTION
    )
)

print(f"Created version: {version.title}")

Add API Definition

from azure.mgmt.apicenter.models import ApiDefinition

definition = client.api_definitions.create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-api-center",
    workspace_name="default",
    api_name="my-api",
    version_name="v1",
    definition_name="openapi",
    resource=ApiDefinition(
        title="OpenAPI Definition",
        description="OpenAPI 3.0 specification"
    )
)

Import API Specification

from azure.mgmt.apicenter.models import ApiSpecImportRequest, ApiSpecImportSourceFormat

# Import from inline content
client.api_definitions.import_specification(
    resource_group_name="my-resource-group",
    service_name="my-api-center",
    workspace_name="default",
    api_name="my-api",
    version_name="v1",
    definition_name="openapi",
    body=ApiSpecImportRequest(
        format=ApiSpecImportSourceFormat.INLINE,
        value='{"openapi": "3.0.0", "info": {"title": "My API", "version": "1.0"}, "paths": {}}'
    )
)

List APIs

apis = client.apis.list(
    resource_group_name="my-resource-group",
    service_name="my-api-center",
    workspace_name="default"
)

for api in apis:
    print(f"{api.name}: {api.title} ({api.kind})")

Create Environment

from azure.mgmt.apicenter.models import Environment, EnvironmentKind

environment = client.environments.create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-api-center",
    workspace_name="default",
    environment_name="production",
    resource=Environment(
        title="Production",
        description="Production environment",
        kind=EnvironmentKind.PRODUCTION,
        server={"type": "Azure API Management", "management_portal_uri": ["https://portal.azure.com"]}
    )
)

Create Deployment

from azure.mgmt.apicenter.models import Deployment, DeploymentState

deployment = client.deployments.create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-api-center",
    workspace_name="default",
    api_name="my-api",
    deployment_name="prod-deployment",
    resource=Deployment(
        title="Production Deployment",
        description="Deployed to production APIM",
        environment_id="/workspaces/default/environments/production",
        definition_id="/workspaces/default/apis/my-api/versions/v1/definitions/openapi",
        state=DeploymentState.ACTIVE,
        server={"runtime_uri": ["https://api.example.com"]}
    )
)

Define Custom Metadata

from azure.mgmt.apicenter.models import MetadataSchema

metadata = client.metadata_schemas.create_or_update(
    resource_group_name="my-resource-group",
    service_name="my-api-center",
    metadata_schema_name="data-classification",
    resource=MetadataSchema(
        schema='{"type": "string", "title": "Data Classification", "enum": ["public", "internal", "confidential"]}'
    )
)

Client Types

ClientPurpose
ApiCenterMgmtClientMain client for all operations

Operations

Operation GroupPurpose
servicesAPI Center service management
workspacesWorkspace management
apisAPI registration and management
api_versionsAPI version management
api_definitionsAPI definition management
deploymentsDeployment tracking
environmentsEnvironment management
metadata_schemasCustom metadata definitions

Best Practices

  1. Use workspaces to organize APIs by team or domain
  2. Define metadata schemas for consistent governance
  3. Track deployments to understand where APIs are running
  4. Import specifications to enable API analysis and linting
  5. Use lifecycle stages to track API maturity
  6. Add contacts for API ownership and support

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

Signals

GitHub stars
265
Forks
26
Last commit
Sep 2026

ahel review

  • S4info
    community integration — published by benjaminastera, not azure

Automated review, not a security audit. Ruleset v1.

Advanced
Catalog kind
skill
Gateway key
azure-mgmt-apicenter-py
Source
github.com/benjaminastera/antigravity-awesome-skills