部署与运维

azure-aigateway

microsoft/azure-skills

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.

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安装命令

npx skills add https://github.com/microsoft/azure-skills --skill azure-aigateway

要点

Configure Azure API Management as an AI Gateway for models, MCP tools, and agents with built-in governance policies.

  • Supports semantic caching (60-80% cost savings), token rate limiting, content safety filtering, and jailbreak detection across AI backends
  • Add Azure OpenAI, AI Foundry models, or convert existing APIs to MCP tools as managed backends with load balancing
  • Includes five core policy categories: authentication, semantic cache lookup, token limits, content safety, and token metrics for observability
  • Requires Azure CLI for configuration and testing; integrates with managed identity for secure backend access

SKILL.md

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