App Service Easy MCP: Add AI Agent Capabilities to Your Existing Apps with Zero Code Changes

The age of AI agents is here. Tools like GitHub Copilot, Claude, and other AI assistants are no longer just answering questions—they're taking actions, calling APIs, and automating complex workflows. But how do you make your existing applications and APIs accessible to these intelligent agents?

At Microsoft Ignite, I teamed up to present session BRK116: Apps, agents, and MCP is the AI innovation recipe, where I demonstrated how you can add agentic capabilities to your existing applications with little to no code changes. Today, I'm excited to share a concrete example of that vision: Easy MCP—a way to expose any REST API to AI agents with absolutely zero code changes to your existing apps.

The Challenge: Bridging REST APIs and AI Agents

Most organizations have invested years building REST APIs that power their applications. These APIs represent critical business logic, data access patterns, and integrations. But AI agents speak a different language—they use protocols like Model Context Protocol (MCP) to discover and invoke tools.

The traditional approach would require you to:

1. Learn the MCP SDK
2. Write new MCP server code
3. Manually map each API endpoint to an MCP tool
4. Deploy and maintain additional infrastructure

What if you could skip all of that?

Introducing Easy MCP (a proof of concept not associated with the App Service platform)

Easy MCP is an OpenAPI-to-MCP translation layer that automatically generates MCP tools from your existing REST APIs. If your API has an OpenAPI (Swagger) specification—which most modern APIs do—you can make it accessible to AI agents in minutes. This means that if you have existing apps with OpenAPI specifications already running on App Service, or really any hosting platform, this tool makes enabling MCP seamless.

How It Works

1. Point the gateway at your API's base URL
2. Detect your OpenAPI specification automatically
3. Connect and the gateway generates MCP tools for every endpoint
4. Use the MCP endpoint URL with any MCP-compatible AI client

That's it. No code changes. No SDK integration. No manual tool definitions.

See It in Action

Let's say you have a Todo API running on Azure App Service at `https://my-todo-app.azurewebsites.net`. In just a few clicks:

1. Open the Easy MCP web UI
2. Enter your API URL
3. Click "Detect" to find your OpenAPI spec
4. Click "Connect"

Now configure your AI client (like VS Code with GitHub Copilot) to use the gateway's MCP endpoint:

{
  "servers": {
    "my-api": {
      "type": "http",
      "url": "https://my-gateway.azurewebsites.net/mcp"
    }
  }
}

Instantly, your AI assistant can:

• "What's on my todo list?"
• "Add 'Review PR #123' to my todos with high priority"
• "Mark all tasks as complete"

All powered by your existing REST API, with zero modifications.

The Bigger Picture: Modernization Without Rewrites

This approach aligns perfectly with a broader modernization strategy we're enabling on Azure App Service.

App Service Managed Instance: Move and Modernize Legacy Apps

For organizations with legacy applications—whether they're running on older Windows frameworks, custom configurations, or traditional hosting environments—Azure App Service Managed Instance provides a path to the cloud with minimal friction. You can migrate these applications to a fully managed platform without rewriting code.

Easy MCP: Add AI Capabilities Post-Migration

Once your legacy applications are running on App Service, Easy MCP becomes the next step in your modernization journey. That 10-year-old internal API? It can now be accessed by AI agents. That legacy inventory system? AI assistants can query and update it. No code changes needed.

The modernization path:

1. Migrate legacy apps to App Service with Managed Instance (no code changes)
2. Expose APIs to AI agents with Easy MCP Gateway (no code changes)
3. Empower your organization with AI-assisted workflows

Deploy It Yourself

Easy MCP is open source and ready to deploy. If you already have an existing API to use with this tool, go for it. If you need an app to test with, check out this sample. Make sure you complete the "Add OpenAPI functionality to your web app" step. You don't need to go beyond that.

GitHub Repository: seligj95/app-service-easy-mcp

Deploy to Azure in minutes with Azure Developer CLI:

azd auth login
azd init
azd up

Or run it locally for testing:

npm install
npm run dev
# Open http://localhost:3000

What's Next: Native App Service Integration

Here's where it gets really exciting.

We're exploring ways to build this capability directly into the Azure App Service platform so you won't have to deploy a second app or additional resources to get this capability. Azure API Management recently released a feature with functionality to expose a REST API, including an API on App Service, as an MCP server, which I highly recommend that you check out if you're familiar with Azure API Management. But in this case, imagine a future where adding AI agent capabilities to your App Service apps is as simple as flipping a switch in the Azure Portal—no gateway or API Management deployment required, no additional infrastructure or services to manage, and built-in security, monitoring, scaling, etc.—all of the features you're already using and are familiar with on App Service.

Stay tuned for updates as we continue to make Azure App Service the best platform for AI-powered applications. And please share your feedback on Easy MCP—we want to hear how you're using it and what features you'd like to see next as we consider this feature for native integration.