Registry indexed
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,
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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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.
| 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" |
| 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 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>
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}'
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>
Recommended policy order in <inbound>:
See references/policies.md for complete example.
| 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.
name: azure-aigateway description: "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." license: MIT metadata: author: Microsoft version: "0.0.0-placeholder" compatibility: Requires Azure CLI (az) for configuration and testing
---
name: azure-aigateway
description: "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."
license: MIT
metadata:
author: Microsoft
version: "0.0.0-placeholder"
compatibility: Requires Azure CLI (az) for configuration and testing
---
# 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](https://learn.microsoft.com/azure/api-management/get-started-create-service-instance).
## 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
```bash
# 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
```bash
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](references/patterns.md#pattern-1-add-ai-model-backend) for full steps.
```bash
# 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>`:
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](https://github.com/Azure-Samples/AI-Gateway)
- [GenAI Gateway Docs](https://learn.microsoft.com/azure/api-management/genai-gateway-capabilities)
## 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)
Skill source recorded
Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.
Review before install: Avoid automatic install
License: MIT
Listed tools are metadata hints, not tested compatibility. Agent prompts are suggested handoffs.
Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.
Version reported in registry metadata; check source releases before relying on it.
Quality
71/100
Strong
Trust
59/100
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
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