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azure-aigateway▌

microsoft/azure-skills · updated Apr 8, 2026

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

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
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

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>:

  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 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

SDK Quick References

how to use azure-aigateway

How to use azure-aigateway on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • ›Cursor installed and configured on your development machine
  • ›Node.js version 16.0+ with npm package manager (verify with node --version)
  • ›Active project directory or workspace where you want to add azure-aigateway
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

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

The skills CLI fetches azure-aigateway from GitHub repository microsoft/azure-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/azure-aigateway

Reload or restart Cursor to activate azure-aigateway. Access the skill through slash commands (e.g., /azure-aigateway) or your agent's skill management interface.

⚠

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

Additional Resources

›View source code on GitHub›Skills CLI documentation›Learn more about Cursor›What are agent skills?

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases▌

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

✓

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

✓

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

✓

Improve work quality by 30-40% with less effort

Implementation Guide▌

Prerequisites

  • ›Claude Desktop or compatible AI client with skill support
  • ›Clear understanding of task or problem to solve
  • ›Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • ⚠Expecting perfect results without iteration
  • ⚠Not providing enough context in prompts
  • ⚠Using skill for tasks outside its intended scope
  • ⚠Accepting outputs without review and validation

Best Practices▌

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • −Don't use without understanding skill limitations
  • −Don't skip validation of outputs
  • −Don't share sensitive information in prompts
  • −Don't expect skill to replace human judgment

💡 Pro Tips

  • ★Be specific about desired format and style
  • ★Ask for multiple options to choose from
  • ★Request explanations to understand reasoning
  • ★Combine AI efficiency with human expertise

When to Use This▌

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path▌

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.6★★★★★47 reviews
  • ★★★★★Nia Liu· Dec 28, 2024

    azure-aigateway is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • ★★★★★Diya Martin· Dec 28, 2024

    azure-aigateway fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • ★★★★★Ganesh Mohane· Dec 16, 2024

    Keeps context tight: azure-aigateway is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • ★★★★★Aditi Zhang· Dec 12, 2024

    azure-aigateway reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • ★★★★★Aditi Liu· Nov 19, 2024

    Solid pick for teams standardizing on skills: azure-aigateway is focused, and the summary matches what you get after install.

  • ★★★★★James Abbas· Nov 19, 2024

    Registry listing for azure-aigateway matched our evaluation — installs cleanly and behaves as described in the markdown.

  • ★★★★★Ira Rao· Nov 11, 2024

    Useful defaults in azure-aigateway — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • ★★★★★Sakshi Patil· Nov 7, 2024

    azure-aigateway has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • ★★★★★Min Martinez· Nov 3, 2024

    We added azure-aigateway from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • ★★★★★Chaitanya Patil· Oct 26, 2024

    Solid pick for teams standardizing on skills: azure-aigateway is focused, and the summary matches what you get after install.

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