🎯

azure-aigateway

🎯Skill

Helps you send all requests to your AI models and tools through Azure API Management, so you can control cost, block harmful content and limit traffic. It includes Azure command-line steps for setup and testing.

microsoft/azure-skills696,591 InstallsAdded Mar 4, 2026

Installation

$npx skills add microsoft/azure-skills --skill azure-aigateway

Run it in a terminal; it asks which AI coding tools to install it for (Claude Code, Codex, Cursor and more).

Uses skills.sh · Node.js 22.20+

After installing

Ask for related work and the agent uses it on its own, or call it yourself.

Run it (Claude Code)/azure-aigateway

Install by hand

Copy the whole skill folder from GitHub to the place below. Copying only SKILL.md can leave out files the skill uses.

Open the skill folder →

This project .claude/skills/azure-aigateway/
All projects ~/.claude/skills/azure-aigateway/

These paths are for Claude Code. For other tools, the command above puts it in the right place.

📦Same repositorymicrosoft/azure-skills (51 items)

What this skill does

Overview

This skill sets up Azure API Management (APIM) as an AI gateway. An AI gateway is a single entry point that every request to your AI models, MCP tools (tools that AI agents can call) and agents passes through. You add policies, which are rules such as token limits or content checks, at this entry point and set everything up with the az command-line tool.

Key Features

Connect Azure OpenAI or AI Foundry models to the gateway and give it access with a managed identity (an Azure login for the service itself).
Limit how many tokens (the units AI models count text in) can be used per minute, and reuse earlier answers to similar questions with semantic caching.
Filter harmful content and detect jailbreak attempts, which are requests that try to make the AI ignore its rules.
Protect MCP tools with request rate limits and record token use as metrics.
Test the gateway with curl and find fixes for common errors such as 429 and 401.

Who is this for?

Use it when several apps share Azure OpenAI models and you need to control their cost and token use. It also fits when you must add safety filters or rate limits before your AI tools go live.

Summarized by AI from this skill's SKILL.md. Suggest a better one

SKILL.md

View on GitHub →

Configure Azure API Management as an AI Gateway for AI models, MCP tools, and agents. WHEN: semantic caching, token limit, content safety, load balancing, AI model governance, MCP rate limiting, jailbreak detection, add Azure OpenAI backend, add AI Foundry model, test AI gateway, LLM policies, configure AI backend, token metrics, AI cost control, convert API to MCP, import OpenAPI to gateway.

Azure AI Gateway

Configure Azure API Management (APIM) as an AI Gateway for governing AI models, MCP tools, and agents.

To deploy APIM, use the azure-prepare skill. See APIM deployment guide.

When to Use This Skill

Category	Triggers
Model Governance	"semantic caching", "token limits", "load balance AI", "track token usage"
Tool Governance	"rate limit MCP", "protect my tools", "configure my tool", "convert API to MCP"
Agent Governance	"content safety", "jailbreak detection", "filter harmful content"
Configuration	"add Azure OpenAI backend", "configure my model", "add AI Foundry model"
Testing	"test AI gateway", "call OpenAI through gateway"

Quick Reference

Policy	Purpose	Details
`azure-openai-token-limit`	Cost control	Model Policies
`azure-openai-semantic-cache-lookup/store`	60-80% cost savings	Model Policies
`azure-openai-emit-token-metric`	Observability	Model Policies
`llm-content-safety`	Safety & compliance	Agent Policies
`rate-limit-by-key`	MCP/tool protection	Tool Policies

Get Gateway Details

# Get gateway URL
az apim show --name <apim-name> --resource-group <rg> --query "gatewayUrl" -o tsv

# List backends (AI models)
az apim backend list --service-name <apim-name> --resource-group <rg> \
  --query "[].{id:name, url:url}" -o table

# Get subscription key
az apim subscription keys list \
  --service-name <apim-name> --resource-group <rg> --subscription-id <sub-id>

Test AI Endpoint

GATEWAY_URL=$(az apim show --name <apim-name> --resource-group <rg> --query "gatewayUrl" -o tsv)

curl -X POST "${GATEWAY_URL}/openai/deployments/<deployment>/chat/completions?api-version=2024-02-01" \
  -H "Content-Type: application/json" \
  -H "Ocp-Apim-Subscription-Key: <key>" \
  -d '{"messages": [{"role": "user", "content": "Hello"}], "max_tokens": 100}'

Common Tasks

Add AI Backend

See references/patterns.md for full steps.

# Discover AI resources
az cognitiveservices account list --query "[?kind=='OpenAI']" -o table

# Create backend
az apim backend create --service-name <apim> --resource-group <rg> \
  --backend-id openai-backend --protocol http --url "https://<aoai>.openai.azure.com/openai"

# Grant access (managed identity)
az role assignment create --assignee <apim-principal-id> \
  --role "Cognitive Services User" --scope <aoai-resource-id>

Apply AI Governance Policy

Recommended policy order in <inbound>:

Authentication - Managed identity to backend
Semantic Cache Lookup - Check cache before calling AI
Token Limits - Cost control
Content Safety - Filter harmful content
Backend Selection - Load balancing
Metrics - Token usage tracking

See references/policies.md for complete example.

Troubleshooting

Issue	Solution
Token limit 429	Increase `tokens-per-minute` or add load balancing
No cache hits	Lower `score-threshold` to 0.7
Content false positives	Increase category thresholds (5-6)
Backend auth 401	Grant APIM "Cognitive Services User" role

See references/troubleshooting.md for details.

References

Detailed Policies - Full policy examples
Configuration Patterns - Step-by-step patterns
Troubleshooting - Common issues
AI-Gateway Samples
GenAI Gateway Docs

SDK Quick References

Content Safety: Python | TypeScript
API Management: Python | .NET

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