What is the recommended Azure SKU for this skill?

The skill defaults to the APIM Basicv2 SKU because it is cost-effective, deploys in approximately 5-10 minutes, and supports all essential GenAI gateway policies.

Can this skill be used to protect non-Azure AI models?

Yes, while it features deep integration with Azure OpenAI and AI Foundry, the gateway patterns can be applied to any AI backend or tool reachable via HTTP.

Does this skill support Model Context Protocol (MCP)?

Yes, it includes specific patterns to convert existing APIs into MCP servers and protect those servers with robust rate limiting and authentication.

Can I use managed identities for authentication?

Yes, the skill provides specific patterns to replace static API keys with Azure Managed Identities for more secure, credential-free backend authentication.

How does semantic caching benefit my AI application?

Semantic caching uses embeddings to identify similar prompts; it serves cached results for equivalent queries to drastically reduce LLM token costs and response latency.

Azure AI Gateway Manager

Name: Azure AI Gateway Manager
Author: microsoft

bymicrosoft

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1,777

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クラウドインフラストラクチャ

Configures Azure API Management to secure, observe, and control AI models and MCP servers with rate limiting and semantic caching.

The Azure AI Gateway skill empowers developers to quickly bootstrap and manage Azure API Management (APIM) as a specialized gateway for generative AI workloads. It provides automated patterns for implementing production-grade infrastructure, including token-based rate limiting, semantic caching to reduce costs, and content safety filters. Whether you are deploying Azure OpenAI models, managing MCP servers, or building complex AI agents, this skill ensures your AI endpoints are secure, observable, and optimized for performance through standardized Bicep templates and XML policies.

主な機能

01Bootstrap Azure APIM instances using the cost-optimized Basicv2 SKU

02Automate load balancing and failover across multiple AI backend providers

03Configure token-based rate limiting to prevent model abuse and overages

04Deploy content safety policies to filter harmful prompts and responses

05Implement semantic caching to reduce LLM latency and API costs

061,777 GitHub stars

ユースケース

01Securing enterprise Azure OpenAI deployments with centralized governance

02Exposing existing internal APIs as protected MCP servers for AI agents

03Implementing global token quotas and usage monitoring across multiple teams

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add microsoft/skills azure-aigateway

For use in Claude.ai and ChatGPT

Download Skill