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sickn33/agentic-awesome-skills/azure-mgmt-apicenter-py

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version: "1.0.0" name: azure-mgmt-apicenter-py description: Azure API Center Management SDK for Python. Use for managing API inventory, metadata, and governance across your organization. risk: critical source: community date_added: '2026-02-27'

Azure API Center Management SDK for Python

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

Installation

bash

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

Environment Variables

bash

AZURE_SUBSCRIPTION_ID=your-subscription-id

Authentication

python

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

python

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

python

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

Register an API

python

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

python

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

python

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

python

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

python

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

python

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

python

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

python

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

Client	Purpose
`ApiCenterMgmtClient`	Main client for all operations

Operations

Operation Group	Purpose
`services`	API Center service management
`workspaces`	Workspace management
`apis`	API registration and management
`api_versions`	API version management
`api_definitions`	API definition management
`deployments`	Deployment tracking
`environments`	Environment management
`metadata_schemas`	Custom metadata definitions

Best Practices

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

When to Use

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

Limitations

Use this skill only when the task clearly matches the scope described above.
Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

All versions