> ## Documentation Index
> Fetch the complete documentation index at: https://www.truefoundry.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Create an OAuth MCP Server with Azure Entra ID

> Learn how to create and deploy an OAuth2-authenticated MCP server using Azure Entra ID and fastMCP, then integrate it with TrueFoundry AI Gateway.

This guide demonstrates how to write a MCP server, add OAuth based authentication to it using Azure Entra ID (formerly Azure AD) as the identity provider and then integrate it with the TrueFoundry gateway. The setup below explains both the user authentication and machine-to-machine authentication scenarios:

* **User Authentication**: Authenticate specific users through the AI Gateway using the Authorization Code flow with refresh tokens
* **Machine-to-Machine Authentication**: Enable programmatic access without user interaction using the Client Credentials grant flow

<Info>
  The entire code for the steps described below can be found in this Github link: [https://github.com/truefoundry/getting-started-examples/tree/main/calculator-oauth-mcp-server](https://github.com/truefoundry/getting-started-examples/tree/main/calculator-oauth-mcp-server)
</Info>

<Note>
  If callers already have an Entra **user** access token and you need the Gateway to exchange it for a Entra-protected MCP token via **On-Behalf-Of**, see [Azure Entra On-Behalf-Of (OBO) for MCP](/docs/ai-gateway/mcp/mcp-server-oauth-azure-obo).
</Note>

## Guide to creating the MCP server and adding OAuth

<Steps>
  <Step title="Write a basic MCP Server and test it locally">
    Let's start by writing a basic MCP server that provides a `get_me` tool.

    ```python server.py expandable lines theme={"dark"}
    from fastmcp import FastMCP

    mcp = FastMCP("Demo 🚀")

    @mcp.tool
    def add(a: int, b: int) -> int:
        """Add two numbers"""
        return a + b

    @mcp.tool
    def subtract(a: int, b: int) -> int:
        """Subtract two numbers"""
        return a - b

    if __name__ == "__main__":
        mcp.run(transport="streamable-http", stateless_http=True)
    ```

    Run the server locally:

    ```bash theme={"dark"}
    python server.py
    ```

    Your MCP server will be available at `http://localhost:8000/mcp`. Test the server using this Python script:

    ```python test.py theme={"dark"}
    import asyncio
    from fastmcp import Client

    async def main():
        async with Client("http://127.0.0.1:8000/mcp") as client:
            tools = await client.list_tools()
            print(tools)
            result = await client.call_tool(
                name="add", 
                arguments={"a": 1, "b": 2}
            )
            print(result)

    asyncio.run(main())
    ```

    This MCP server is running without any authentication. Enable OAuth next by registering the server in Microsoft Entra ID, then adding JWT verification to the code.
  </Step>

  <Step title="Register the MCP server in Microsoft Entra ID">
    Create the resource app, expose scopes, create the client app, and grant API permissions. Follow [Microsoft Entra app setup](/docs/ai-gateway/mcp/entra-app-setup) and collect tenant ID, audience (API client ID), client ID, client secret, issuer, JWKS URI, and custom scopes (`api://{API_CLIENT_ID}/...` plus `offline_access`).
  </Step>

  <Step title="Modify MCP server code to add OAuth Token verification">
    Create a .env file to add the environment variables and modify the server.py file to add the JWT verification.

    <CodeGroup>
      ```python server.py highlight={6-22} theme={"dark"}
      from fastmcp import FastMCP
      import os
      from fastmcp.server.auth.providers.jwt import JWTVerifier
      from dotenv import load_dotenv
      from starlette.requests import Request
      from starlette.responses import RedirectResponse

      load_dotenv()

      # Configure JWT verification using JWKS
      token_verifier = JWTVerifier(
          jwks_uri=os.getenv("OAUTH_JWKS_URI"),
          issuer=os.getenv("OAUTH_ISSUER"),
          audience=os.getenv("OAUTH_AUDIENCE"),
      )

      # Bearer token authentication
      mcp = FastMCP("Demo 🚀", auth=token_verifier)

      # Forward .well-known/oauth-authorization-server to Azure's OpenID configuration
      @mcp.custom_route("/.well-known/oauth-authorization-server", methods=["GET", "HEAD", "OPTIONS"], include_in_schema=False)
      async def oauth_well_known(request: Request):
          """Redirect to Azure's OpenID configuration endpoint."""
          return RedirectResponse(os.environ.get("OAUTH_ISSUER") + "/.well-known/openid-configuration", status_code=307)

      @mcp.tool
      def add(a: int, b: int) -> int:
          """Add two numbers"""
          return a + b

      @mcp.tool
      def subtract(a: int, b: int) -> int:
          """Subtract two numbers"""
          return a - b

      if __name__ == "__main__":
          mcp.run(transport="streamable-http", host="0.0.0.0", port=8000, stateless_http=True)
      ```

      ```yaml .env theme={"dark"}
      OAUTH_JWKS_URI=https://login.microsoftonline.com/{TENANT_ID}/discovery/v2.0/keys
      OAUTH_ISSUER=https://login.microsoftonline.com/{TENANT_ID}/v2.0
      OAUTH_AUDIENCE={API_CLIENT_ID}
      ```
    </CodeGroup>

    <Note>
      Replace `{TENANT_ID}` with your Azure tenant ID and `{API_CLIENT_ID}` with the Application ID of your CalculatorMCPServer app registration.

      **Important**: The audience should be just the client ID (e.g., `15a6b7c9-1b09-4e1a-9f38-53db81e18b05`), not the full `api://` URI. Azure tokens contain only the client ID in the `aud` claim.
    </Note>
  </Step>

  <Step title="Get the token and call the MCP server in test.py (Machine-to-Machine authentication)">
    In Step 1, we had a script to test the MCP server locally. After adding the OAuth token verification to the MCP server in the previous step, we need to modify the script to get the token and then call the MCP server. If you call the MCP server without a token, it will return a 401 Unauthorized error.

    ```python test.py theme={"dark"}
    import asyncio
    from fastmcp import Client
    import requests

    # Configuration
    TENANT_ID = "12345678-1234-1234-1234-123456789abc"
    TOKEN_ENDPOINT = f"https://login.microsoftonline.com/{TENANT_ID}/oauth2/v2.0/token"
    CLIENT_ID = "abcdef12-3456-7890-abcd-ef1234567890"
    CLIENT_SECRET = "your-client-secret"
    SCOPE = "api://9876543-5678-5678-5678-987654321def/.default"  # Note: .default for client credentials

    # Request token
    response = requests.post(
        TOKEN_ENDPOINT,
        data={
            "grant_type": "client_credentials",
            "client_id": CLIENT_ID,
            "client_secret": CLIENT_SECRET,
            "scope": SCOPE
        }
    )

    print(response.json())
    response.raise_for_status()
    token_data = response.json()
    access_token = token_data["access_token"]

    print(f"Access Token: {access_token}")
    print(f"Expires in: {token_data['expires_in']} seconds")

    # Call the MCP server
    async def main():
        async with Client("http://localhost:8000/mcp", auth=access_token) as client:
            tools = await client.list_tools()
            print(tools)
            result = await client.call_tool(
                name="add", 
                arguments={"a": 1, "b": 2}
            )
            print(result)

    asyncio.run(main())
    ```

    <Note>
      For client credentials flow with Azure Entra ID, use the scope format `api://{client-id}/.default` to request all application permissions. The token will contain the short scope names (e.g., `calculator.add calculator.subtract`) in the `scp` claim, but you request them using the `.default` suffix.
    </Note>

    This is exactly how you will be doing Machine-to-Machine authentication to the MCP server. Code snippets to get the token in different ways are outlined below:

    <Tabs>
      <Tab title="Using cURL">
        ```bash theme={"dark"}
        # Set your values
        TENANT_ID="12345678-1234-1234-1234-123456789abc"
        TOKEN_ENDPOINT="https://login.microsoftonline.com/${TENANT_ID}/oauth2/v2.0/token"
        CLIENT_ID="abcdef12-3456-7890-abcd-ef1234567890"
        CLIENT_SECRET="your-client-secret"
        SCOPE="api://9876543-5678-5678-5678-987654321def/.default"

        # Request access token
        curl -X POST "${TOKEN_ENDPOINT}" \
          -H "Content-Type: application/x-www-form-urlencoded" \
          -d "grant_type=client_credentials" \
          -d "client_id=${CLIENT_ID}" \
          -d "client_secret=${CLIENT_SECRET}" \
          -d "scope=${SCOPE}"
        ```

        Response:

        ```json theme={"dark"}
        {
          "token_type": "Bearer",
          "expires_in": 3599,
          "ext_expires_in": 3599,
          "access_token": "eyJ0eXAiOiJKV1QiLCJhbGc..."
        }
        ```

        <Note>
          Azure Entra ID uses `scope` parameter (not `audience`) and requires the `.default` suffix for client credentials flow.
        </Note>
      </Tab>

      <Tab title="Using Python">
        ```python theme={"dark"}
        import requests

        # Configuration
        TENANT_ID = "12345678-1234-1234-1234-123456789abc"
        TOKEN_ENDPOINT = f"https://login.microsoftonline.com/{TENANT_ID}/oauth2/v2.0/token"
        CLIENT_ID = "abcdef12-3456-7890-abcd-ef1234567890"
        CLIENT_SECRET = "your-client-secret"
        SCOPE = "api://9876543-5678-5678-5678-987654321def/.default"

        # Request token
        response = requests.post(
            TOKEN_ENDPOINT,
            data={
                "grant_type": "client_credentials",
                "client_id": CLIENT_ID,
                "client_secret": CLIENT_SECRET,
                "scope": SCOPE
            }
        )

        response.raise_for_status()
        token_data = response.json()
        access_token = token_data["access_token"]

        print(f"Access Token: {access_token}")
        print(f"Expires in: {token_data['expires_in']} seconds")
        ```
      </Tab>

      <Tab title="Using Python with MSAL">
        ```python theme={"dark"}
        from msal import ConfidentialClientApplication

        # Configuration
        TENANT_ID = "12345678-1234-1234-1234-123456789abc"
        CLIENT_ID = "abcdef12-3456-7890-abcd-ef1234567890"
        CLIENT_SECRET = "your-client-secret"
        AUTHORITY = f"https://login.microsoftonline.com/{TENANT_ID}"
        SCOPE = ["api://9876543-5678-5678-5678-987654321def/.default"]

        # Create MSAL app
        app = ConfidentialClientApplication(
            CLIENT_ID,
            authority=AUTHORITY,
            client_credential=CLIENT_SECRET
        )

        # Acquire token
        result = app.acquire_token_for_client(scopes=SCOPE)

        if "access_token" in result:
            access_token = result["access_token"]
            print(f"Access Token: {access_token}")
            print(f"Expires in: {result['expires_in']} seconds")
        else:
            print(f"Error: {result.get('error')}")
            print(f"Description: {result.get('error_description')}")
        ```
      </Tab>
    </Tabs>
  </Step>

  <Step title="Host the MCP server and get the endpoint URL">
    Now that we have tested the MCP server locally, we will add it to the AI Gateway to enable user authentication and allow the MCP server to be accessed via the AI Gateway.
    To add the MCP server to the AI Gateway, we need to get the endpoint URL of the MCP server. Hence, we need to host the MCP server on a public URL.

    <Tip>
      If you are using the TrueFoundry AI Deployment product, this can be done by creating a service deployment, choosing your Github repository containing the MCP server code above. Otherwise, you can host it on a VM or a Kubernetes cluster or any hosting provider of your choice.
    </Tip>

    Remember to add the environment variables for the MCP server:

    | Variable         | Value                                                               | Description                                               |
    | ---------------- | ------------------------------------------------------------------- | --------------------------------------------------------- |
    | `OAUTH_JWKS_URI` | `https://login.microsoftonline.com/{TENANT_ID}/discovery/v2.0/keys` | JSON Web Key Set URI for token verification               |
    | `OAUTH_ISSUER`   | `https://login.microsoftonline.com/{TENANT_ID}/v2.0`                | Azure Entra ID issuer URI                                 |
    | `OAUTH_AUDIENCE` | `{API_CLIENT_ID}`                                                   | Application (client) ID of your CalculatorMCPServer (API) |

    <Note>
      The MCP server only needs these environment variables to validate OAuth tokens. It doesn't need the Client ID or Client Secret since it's only validating tokens, not generating them.
    </Note>

    After deployment, you will have the endpoint URL of the MCP server. Let's consider it `https://calculator-oauth-mcp-server.example.com` for the rest of the steps.
    After deploying, check once using the test.py script above by changing the MCP server URL to the deployed URL. You should be able to fetch the tools from the MCP server.
  </Step>

  <Step title="Add the MCP server to the TrueFoundry AI Gateway">
    <Note>
      You will need to have a MCP server group to be able to add the MCP server to the TrueFoundry AI Gateway. Please refer to the [Getting Started](/docs/ai-gateway/mcp/mcp-server-getting-started) guide to create a MCP server group.
    </Note>

    1. In your MCP Server Group, click **Add MCP Server**

    2. Select **Remote MCP**

    3. Configure the server:
       * **Name**: `calculator-mcp-azure-oauth`
       * **Description**: OAuth-authenticated MCP server with Azure Entra ID
       * **URL**: Your deployed service endpoint (e.g., `https://calculator-oauth-mcp-server.example.com/mcp`)
       * **Transport**: `streamable-http`
       * **Authentication Type**: Select **OAuth2**

    4. In the OAuth2 configuration section, provide the Azure credentials:
       * **OAuth2 Client ID**: Your CalculatorMCPClient application client ID
       * **OAuth2 Client Secret**: Your CalculatorMCPClient client secret

    <Note>
      The AI Gateway will automatically discover the OAuth2 Authorization URL, Token URL, and other configuration details from your MCP server's `/.well-known/oauth-authorization-server` endpoint once you provide the MCP server URL.

      **Important - Azure Custom Scopes**:
      Azure's well-known endpoint only includes generic OpenID scopes (`openid`, `profile`, `email`, `offline_access`). You **must manually add your custom API scopes** in the OAuth2 configuration:

      * **OAuth2 Scopes**: Manually enter your scopes in the format:
        * `api://{API_CLIENT_ID}/calculator.add`
        * `api://{API_CLIENT_ID}/calculator.subtract`
        * `offline_access` (to enable automatic token refresh)

      Replace `{API_CLIENT_ID}` with your **CalculatorMCPServer** Application (client) ID (e.g., `api://15a6b7c9-1b09-4e1a-9f38-53db81e18b05/calculator.add`).

      You can also store the client id and secrets in truefoundry secrets and reference them by FQN in the configuration.
    </Note>

    5. Set **access control**: Select teams or users who should have access to this MCP server

    <Note>
      Managers of the MCP Server Group automatically have access to all servers in the group.
    </Note>

    <img src="https://mintcdn.com/truefoundry/62IaXsiblF4PkZxX/images/azure-oauth-manifest.png?fit=max&auto=format&n=62IaXsiblF4PkZxX&q=85&s=eb53571b04f68fe81d1de99429da7d8c" width="997" height="1190" data-path="images/azure-oauth-manifest.png" />

    6. Click **Save** to add the MCP server
       * The server will appear in your MCP Server Group
       * Users can now connect and use the server through the AI Gateway
  </Step>

  <Step title="Test the MCP server in the Playground">
    1. Navigate to the **Playground** in the AI Gateway
    2. Click **Add Tool/MCP Servers**
    3. Find your `calculator-mcp-azure-oauth` in the list
    4. Click **Connect Now** to initiate OAuth authorization

    <img src="https://mintcdn.com/truefoundry/62IaXsiblF4PkZxX/images/azure-oauth-playground.png?fit=max&auto=format&n=62IaXsiblF4PkZxX&q=85&s=36b5a05002aa9977eb2595b324a8a516" width="1534" height="1351" data-path="images/azure-oauth-playground.png" />

    5. You'll be redirected to Azure to authorize access
    6. Sign in with your Azure account and consent to the requested permissions
    7. You'll be redirected back to the AI Gateway
    8. The AI Gateway will store your OAuth tokens securely and refresh them automatically when they expire
    9. You'll see the `add` and `subtract` tools from your MCP server
    10. Select the tools and click **Done**
    11. Try sending a prompt like `Add 1 and 2. Use the tools provided`
    12. The tool will return the result from your MCP server

    <img src="https://mintcdn.com/truefoundry/62IaXsiblF4PkZxX/images/azure-oauth-pg-eg.png?fit=max&auto=format&n=62IaXsiblF4PkZxX&q=85&s=35090cdb1b30796b70ac9f17f5d20536" width="1487" height="782" data-path="images/azure-oauth-pg-eg.png" />
  </Step>
</Steps>