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azure-aigateway

Route and govern AI requests through Azure API Management with configurable policies.

Updated Apr 10, 2026
Search Tags:#rbac#policy#content-safety#ai-gateway#token-metrics#apim#semantic-caching
One-click install
npx skills add https://github.com/attentiondotnet/azure-skills --skill azure-aigateway-attentiondotnet
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: azure-aigateway
Source: https://github.com/attentiondotnet/azure-skills/tree/main/.github/plugins/azure-skills/skills/azure-aigateway
Command: npx skills add https://github.com/attentiondotnet/azure-skills --skill azure-aigateway-attentiondotnet

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Route and govern AI requests through Azure API Management to enforce consistent policies for AI models, MCP tools, and agents.

Core Features & Use Cases

  • Centralized policy enforcement for authentication, token limits, content safety, and rate limiting across AI backends.
  • Seamless integration with MCP tools and Azure OpenAI deployments to standardize governance patterns.
  • Real-world use case: deploy an APIM gateway that enforces governance for multiple AI deployments and tools, while collecting token metrics and semantic cache hints for cost control.

Quick Start

Deploy the APIM governance gateway by configuring backends and applying the policy suite.

Frequently Asked Questions about azure-aigateway

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

FAQPage Schema
How do I enforce rate limiting and content safety policies for Azure OpenAI deployments?▼

Azure API Management enforces rate limiting and content safety policies by routing AI requests through a centralized gateway, applying consistent governance rules across all Azure OpenAI deployments and MCP tools.

What is the best way to collect token metrics and apply semantic caching for AI models?▼

Configuring an Azure API Management AI gateway enables token metrics collection and semantic caching hints, intercepting AI model requests to optimize cost control and standardize governance patterns.

How do I configure authentication and backend selection across multiple AI tools and agents?▼

Deploying an Azure API Management governance gateway configures authentication and backend selection, standardizing access controls and routing traffic across diverse AI deployments and MCP tools.

Do I need Azure CLI to set up an AI gateway for MCP tools and agents?▼

Yes, Azure CLI is required to configure and test the AI gateway, coordinating with azure-prepare and azure-diagnostics skills to deploy and govern AI workflows across MCP tools and agents.

Can I use Azure API Management to govern MCP tools and agents simultaneously?▼

Azure API Management governs MCP tools and agents simultaneously by applying centralized policy enforcement, ensuring consistent authentication, rate limiting, and content safety across all connected AI endpoints.

Why use Azure API Management instead of direct Azure OpenAI endpoints for AI governance?▼

Azure API Management centralizes AI governance instead of relying on direct Azure OpenAI endpoints, enforcing consistent policies, semantic caching, and token metrics collection across all deployments rather than managing individually.

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