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azure-aigateway

Configure Azure API Management as an AI Gateway for AI models and MCP tools.

Updated Apr 19, 2026
Search Tags:#Azure OpenAI#Azure API Management#AI Gateway#MCP Tools#AI Model Governance
One-click install
npx skills add https://github.com/Avihai-H/infraops --skill azure-aigateway-avihai-h
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: azure-aigateway
Source: https://github.com/Avihai-H/infraops/tree/main/.github/skills/azure-aigateway
Command: npx skills add https://github.com/Avihai-H/infraops --skill azure-aigateway-avihai-h

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires az, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides the capability to configure Azure API Management (APIM) as an AI Gateway for governing AI models, MCP tools, and agents, simplifying the management of AI-driven infrastructure.

Core Features & Use Cases

  • AI Model Governance: Configure and manage AI models within APIM, including token limits, semantic caching, and load balancing.
  • MCP Tool Governance: Secure and manage MCP tools with rate limiting and authentication.
  • Agent Governance: Implement content safety and jailbreak detection for agents.
  • Configuration: Add AI model backends, configure models, and manage Azure OpenAI backends.
  • Testing: Test AI gateways and endpoints.

Quick Start

Deploy an AI Gateway by running the following command:

az apim show --name <apim-name> --resource-group <rg> --query "gatewayUrl" -o tsv

Frequently Asked Questions about azure-aigateway

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I configure Azure API Management as an AI Gateway for AI models?▼

To configure an AI Gateway, use this Skill to manage Azure API Management policies for AI models, including adding backends, setting token rate limits, and enabling semantic caching. It requires the Azure CLI to deploy and test the gateway endpoints.

What is AI model governance in Azure API Management?▼

AI model governance in Azure API Management is the process of securing and routing AI traffic. This Skill configures policies like token rate limiting, semantic caching, and load balancing to manage Azure OpenAI backends and agents effectively.

How do I secure MCP tools with rate limiting and authentication?▼

You can secure MCP tools by configuring Azure API Management as an AI Gateway. This Skill applies governance policies, enforcing authentication and rate limiting to protect MCP tools and agents from unauthorized or excessive use.

Do I need Azure CLI to manage AI Gateway policies?▼

Yes, you need the Azure CLI installed to use this Skill. It relies on the az command-line interface to configure Azure API Management, add AI model backends, and retrieve gateway URLs for testing your deployment.

Can I implement content safety and jailbreak detection for agents?▼

Yes, you can implement content safety and jailbreak detection for agents. This Skill configures Azure API Management policies to inspect agent traffic, applying governance rules that filter unsafe content and prevent jailbreak attempts.

What is the best way to load balance Azure OpenAI backends?▼

The best way to load balance Azure OpenAI backends is through Azure API Management. This Skill configures the AI Gateway to distribute traffic across multiple model backends while enforcing token limits and semantic caching for optimal performance.

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