azure-mgmt-apicenter-py
Azure API Center Management SDK for Python. Use for managing API inventory, metadata, and governance across your organization. Triggers: "azure-mgmt-apicenter", "ApiCenterMgmtClient", "API Center", "API inventory", "API governance".
Install / Use
npx skills add microsoft/skills --skill azure-mgmt-apicenter-pyInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Development & EngineeringSupported Platforms
Our assessment of azure-mgmt-apicenter-py
azure-mgmt-apicenter-py scores 93/100 on our quality scale, 560th of 3,481 Development & Engineering skills we index (top 17%).
Its SKILL.md is 9.1 KB long, well organised into 23 sections with 13 code examples: a thorough specification that gives an agent plenty to work with.
With 3,051 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 5 days ago, so azure-mgmt-apicenter-py is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit β read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.
Automated pattern scan on 2026-09-29. It catches known dangerous patterns, not every risk β read a skill before letting an agent act on it.
azure-mgmt-apicenter-py compared with similar skills
All 4 of these similar skills score higher than azure-mgmt-apicenter-py; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| azure-mgmt-apicenter-py (this skill)by microsoft | 93 | 3.1k | 5d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 86.1k | 13d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 74.1k | today | CLAUDE.md |
| ai-job-searchby MadsLorentzen | 100 | 44.4k | today | CLAUDE.md |
| claude-howtoby luongnv89 | 100 | 41.7k | 2d ago | CLAUDE.md |
Frequently asked questions
- How do I install azure-mgmt-apicenter-py?
- Run
npx skills add microsoft/skills --skill azure-mgmt-apicenter-py. The install tabs above show the steps for each supported agent. - Which AI agents does azure-mgmt-apicenter-py work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is azure-mgmt-apicenter-py safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is azure-mgmt-apicenter-py still maintained?
- The repository was last updated 5 days ago, so azure-mgmt-apicenter-py is actively maintained.
Skill content
View source on GitHubname: azure-mgmt-apicenter-py description: | Azure API Center Management SDK for Python. Use for managing API inventory, metadata, and governance across your organization. Triggers: "azure-mgmt-apicenter", "ApiCenterMgmtClient", "API Center", "API inventory", "API governance". license: MIT metadata: author: Microsoft version: "1.0.0" package: azure-mgmt-apicenter
Azure API Center Management SDK for Python
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 # Required for all auth methods
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production
Authentication & Lifecycle
π Two rules apply to every code sample below:
- Prefer
DefaultAzureCredential. It works locally (Azure CLI / VS Code / Developer CLI) and in Azure (managed identity, workload identity) with no code change. Avoid connection strings, account/API keys β they bypass Entra audit and rotation.
- Local dev:
DefaultAzureCredentialworks as-is.- Production: set
AZURE_TOKEN_CREDENTIALS=prod(orAZURE_TOKEN_CREDENTIALS=<specific_credential>) to constrain the credential chain to production-safe credentials.- Wrap every client in a context manager so HTTP transports, sockets, and token caches are released deterministically:
- Sync:
with <Client>(...) as client:- Async:
async with <Client>(...) as client:andasync with DefaultAzureCredential() as credential:(fromazure.identity.aio)Snippets may abbreviate this setup, but production code should always follow both rules.
from azure.identity import DefaultAzureCredential, ManagedIdentityCredential
from azure.mgmt.apicenter import ApiCenterMgmtClient
import os
# Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
credential = DefaultAzureCredential(require_envvar=True)
# Or use a specific credential directly in production:
# See https://learn.microsoft.com/python/api/overview/azure/identity-readme?view=azure-python#credential-classes
# credential = ManagedIdentityCredential()
with ApiCenterMgmtClient(
credential=credential,
subscription_id=os.environ["AZURE_SUBSCRIPTION_ID"]
) as client:
# Use `client` for all subsequent operations (see examples below)
...
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, ApiProperties
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(
properties=ApiProperties(
title="My API",
description="A sample API for demonstration",
kind=ApiKind.REST,
terms_of_service={"url": "https://example.com/terms"},
contacts=[{"name": "API Team", "email": "api-team@example.com"}],
)
),
)
print(f"Registered API: {api.properties.title}")
Create API Version
from azure.mgmt.apicenter.models import ApiVersion, ApiVersionProperties, 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(
properties=ApiVersionProperties(
title="Version 1.0",
lifecycle_stage=LifecycleStage.PRODUCTION,
)
),
)
print(f"Created version: {version.properties.title}")
Add API Definition
from azure.mgmt.apicenter.models import ApiDefinition, ApiDefinitionProperties
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(
properties=ApiDefinitionProperties(
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.begin_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": {}}',
)
).result()
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, EnvironmentProperties
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(
properties=EnvironmentProperties(
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, DeploymentProperties, 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(
properties=DeploymentProperties(
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, MetadataSchemaProperties
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(
properties=MetadataSchemaProperties(
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
- Pick sync OR async and stay consistent. Do not mix
azure.xxxsync clients withazure.xxx.aioasync clients in the same call path. Choose one mode per module. - Always use context managers for clients and async credentials. Wrap every client in
with Client(...) as client:(sync) orasync with Client(...) as client:(async). For asyncDefaultAzureCredentialfromazure.identity.aio, also useasync with credential:so tokens and transports are cleaned up. - 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
Reference Files
| File | Contents | |------|----------| | references/capabilities.md | Additional non-hero capabilities, operation-group coverage, and production checklists. | | references/non-hero-scenarios.md | Dedicated non-hero examples for secondary/advanced scenarios. |
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit β see the Safety scan above for what the skill file itself contains.
