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Azure Aigateway

skill-microsoft-azure-skills-azure-aigateway · by microsoft

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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Install

$ agentstack add skill-microsoft-azure-skills-azure-aigateway

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access Used
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
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1mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

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](references/policies.md#token-rate-limiting) | | azure-openai-semantic-cache-lookup/store | 60-80% cost savings | [Model Policies](references/policies.md#semantic-caching) | | azure-openai-emit-token-metric | Observability | [Model Policies](references/policies.md#token-metrics) | | llm-content-safety | Safety & compliance | [Agent Policies](references/policies.md#content-safety) | | rate-limit-by-key | MCP/tool protection | [Tool Policies](references/policies.md#request-rate-limiting) |


Get Gateway Details

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

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

# Get subscription key
az apim subscription keys list \
  --service-name  --resource-group  --subscription-id 

Test AI Endpoint

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

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

Common Tasks

Add AI Backend

See [references/patterns.md](references/patterns.md#pattern-1-add-ai-model-backend) for full steps.

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

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

# Grant access (managed identity)
az role assignment create --assignee  \
  --role "Cognitive Services User" --scope 

Apply AI Governance Policy

Recommended policy order in ``:

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

See [references/policies.md](references/policies.md#combining-policies) 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](references/troubleshooting.md) for details.


References

  • [Detailed Policies](references/policies.md) - Full policy examples
  • [Configuration Patterns](references/patterns.md) - Step-by-step patterns
  • [Troubleshooting](references/troubleshooting.md) - Common issues
  • AI-Gateway Samples
  • GenAI Gateway Docs

SDK Quick References

  • Content Safety: [Python](references/sdk/azure-ai-contentsafety-py.md) | [TypeScript](references/sdk/azure-ai-contentsafety-ts.md)
  • API Management: [Python](references/sdk/azure-mgmt-apimanagement-py.md) | [.NET](references/sdk/azure-mgmt-apimanagement-dotnet.md)

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.