<!--

name: Remote MCP with Azure Container Apps (Node.js/TypeScript/JavaScript) description: Run a remote node.js MCP server on Azure Container Apps.
languages:

• typescript
• javascript
• nodejs
• bicep
• azdeveloper products:
• azure-container-apps
• azure page_type: sample urlFragment: mcp-container-ts

---

-->

Getting Started with Remote MCP Servers using Azure Container Apps (Node.js/TypeScript)

<div align="center">

<br>

:star: To stay updated and get notified about changes, star this repo on GitHub!

</div>

This is a quick start guide that provides the basic building blocks to set up a remote Model Context Protocol (MCP) server using Azure Container Apps. The MCP server is built using Node.js and TypeScript, and it can be used to run various tools and services in a serverless environment. This project also implements a multi-layered security architecture combining JWT-based authentication with role-based access control (RBAC) to secure the MCP server endpoints and tools.

[!WARNING] Code presented here is for demo purposes only. Your specific scenarios (including rules inside your enterprise, specific security controls, or other protection mechanisms) may differ from the ones that are outlined in this repository. Always conduct a security audit and threat modeling for any production and customer-facing assets that require authentication and authorization.

What is MCP?

The Model Context Protocol (MCP) is an open protocol that allows Large Language Models (LLMs) to interact with external tools and services in a standardized way. MCP enables LLMs to access and utilize various resources, such as databases, APIs, and other services, to enhance their capabilities and provide more accurate and relevant responses.

Below is the architecture diagram for a typical MCP server setup:

flowchart TD
    user(("fa:fa-users User"))
    host["VS Code, Copilot, LlamaIndex, Langchain..."]
    clientHttp[MCP HTTP Client]
    serverHttp([MCP HTTP Server])
    agent["Agents (not included in this demo)"]
    AzureOpenAI([Azure AI Foundry])
    GitHub([GitHub Models])
    OpenAI([OpenAI])
    
    tools["fa:fa-wrench Tools"]
    db[(sqlite DB)]

    user --> hostGroup 
    subgraph hostGroup["MCP Host"]
        host -.- agent
        host aaa@ -.- clientHttp
    end
    
    agent -.- AzureOpenAI & GitHub & OpenAI
    
    clientHttp aa@ ---> |"Streamable HTTP (authenticated)"| serverHttp

    subgraph container["ACA or localhost"]
      serverHttp a@ -.- tools
      tools b@ -.- add_todo 
      tools c@ -.- list_todos
      tools d@ -.- complete_todo
      tools e@ -.- delete_todo
    end

    add_todo bb@ --> db
    list_todos cc@--> db
    complete_todo dd@ --> db
    delete_todo ee@ --> db

    %% styles

    classDef animate stroke-dasharray: 9,5,stroke-dashoffset: 900,animation: dash 25s linear infinite;
    classDef highlight fill:#9B77E8,color:#fff,stroke:#5EB4D8,stroke-width:2px
    
    class a animate
    class aa animate
    class aaa animate
    class b animate
    class c animate
    class d animate
    class e animate
    class bb animate
    class cc animate
    class dd animate
    class ee animate

    class container highlight

Why use Azure Container Apps?

Azure Container Apps is a fully managed, serverless container platform that simplifies the deployment and operation of containerized applications. ACA also provides serverless GPU support, so that you can bring your own containers and deploy them to GPU-backed environments that automatically scale based on demand.

Key benefits:

• Autoscaling – scale to zero when idle, scale out with usage
• Pay-per-second billing – pay only for the compute you use
• Ease of use - accelerate developer velocity and easily bring any container and run it on GPUs in the cloud
• No infrastructure management – focus on your model and app
• Enterprise-grade features – out of the box support for bringing your own virtual networks, managed identity, private endpoints and more with full data governance

Prerequisites

1. Install the latest version of VS Code
2. Install GitHub Copilot and GitHub Copilot Chat extensions

Running the MCP Server Locally

If you prefer to run the MCP server locally, you can do so by following these steps.

You need to have the following tools installed on your local machine:

• git necessary to clone the repository.
• Node.js and npm.

Once you have the prerequisites installed, you can follow these steps to run the MCP server locally:

1. Clone this repository:

git clone https://github.com/Azure-Samples/mcp-container-ts
cd mcp-container-ts

2. Install project dependencies

npm install

3. Generate a new JWT configuration:

npm run generate-token -- --admin

[!NOTE] You can also generate a token with a different role by using the --admin, --user or --readonly flags. The generated token will have different permissions based on the role you choose (see src/auth/authorization.ts for more details).

This will append (or create) a new JWT configuration to .env file at the root of the project. The generated token will be used to authenticate requests to the MCP server.

[!IMPORTANT] In a production environment, you should use a more secure method to manage your secrets and tokens.

4. Start the dev server

npm run dev

You should see the following output in the terminal:

  mcp:db 2025-07-23T16:48:05.381Z PRAGMA journal_mode = WAL +0ms
  mcp:db 2025-07-23T16:48:05.382Z CREATE TABLE IF NOT EXISTS todos (
  mcp:db      id INTEGER PRIMARY KEY AUTOINCREMENT,
  mcp:db      text TEXT NOT NULL,
  mcp:db      completed INTEGER NOT NULL DEFAULT 0
  mcp:db    ) +0ms
  mcp:db 2025-07-23T16:48:05.382Z Database "todos" initialized. +0ms
  mcp:index 2025-07-23T16:48:05.449Z MCP Stateless Streamable HTTP Server +0ms
  mcp:index 2025-07-23T16:48:05.449Z MCP endpoint: http://localhost:3000/mcp +0ms
  mcp:index 2025-07-23T16:48:05.449Z Press Ctrl+C to stop the server +0ms

4. To access and use the MCP server, read the Use your MCP server section below.

<br>

[!NOTE] When the applications starts, the server will create an in-memory SQLite database. This database is used to store the state of the tools and their interactions with the MCP server.

Deploying the MCP Server to Azure Container Apps

To deploy the MCP server to Azure Container Apps, you can use the Azure Developer CLI (azd). This will allow you to provision and deploy the project to Azure with minimal effort:

• Install the Azure Developer CLI.

Once you have the prerequisites installed, you can follow these steps to deploy the MCP server to Azure Container Apps:

1. Clone this repository

git clone https://github.com/azure-samples/mcp-container-ts.git
cd mcp-container-ts

2. Log in to your Azure account

azd auth login

For GitHub Codespaces users, if the previous command fails, try:

azd auth login --use-device-code

1. Provision and deploy the project (ensure you are in the folder of the cloned repo when running this command):

azd up

4. Once the deployment is complete, you can access the MCP server using the URL provided in the output. The URL will look something like this:

https://<env-name>.<container-id>.<region>.azurecontainerapps.io

5. To access and use the MCP server, read the Use your MCP server section below.

[!NOTE] If you were simply testing the deployment, you can remove and clean up all deployed resources by running the following command to avoid incurring any costs:

azd down --purge --force

Other installation options

You have a few other options to get started with this template. The quickest way to get started is GitHub Codespaces, since it will setup all the tools for you and you can run the MCP server in the browser.

GitHub Codespaces

You can run this template virtually by using GitHub Codespaces. The button will open a web-based VS Code instance in your browser:

1. Open the template (this may take several minutes):

   

2. Open a terminal window

3. Continue with the next steps to either run the MCP server locally or deploy it to Azure Container Apps.

[!NOTE] If you run the mcp server inside of GitHub Codespaces, make sure to change the port visibility to Public: Click on "PORTS" tabs → right-click on the opened port (3000 by default) → Port visibility → Public.

VS Code Dev Containers

A related option is VS Code Dev Containers, which will open the project in your local VS Code using the Dev Containers extension:

1. Install Docker Desktop and VS Code Dev Containers extension if not already installed.

2. Start Docker Desktop (install it if not already installed)

3. Open the project:

   

4. Open a terminal window

5. Continue with the next steps to either run the MCP server locally or deploy it to Azure Container Apps.

Use your MCP server

Option 0 - Use the provided Client examples

This repository contains an example that demonstrates how to use the MCP server with OpenAI models. The example is located in the [examples/](./examples/) directory.

Option 1 - Use the mcp.json file in VS Code

The quickest way to connect to the MCP server is the use the provided .vscode/mcp.json configuration file to set up the MCP server in your VS Code environment. This configuration file contains the necessary settings for the MCP server, including the URL and transport type.

{
  "inputs": [
    {
      "password": true,
      "id": "mcp-server-token",
      "description": "Enter the token for the MCP server",
      "type": "promptString",
    }
  ],
  "servers": {
    "mcp-server": {
      "type": "http",
      "url": "http://localhost:3000/mcp",
      "headers": {
        "Authorization": "Bearer ${input:mcp-server-token}"
      }
    },
    "mcp-server-remote": {
      "type": "http",
      "url": "https://<env-name>.<container-id>.<region>.azurecontainerapps.io/mcp",
      "headers": {
        "Authorization": "Bearer ${input:mcp-server-token}"
      }
    }
  }
}

Once you have this file opened, you can click on the "start" inlined action button that will connect the MCP server and fetch the available tools.

IMPORTANT: Because the server is secured with a JWT token, you will be prompted by VS Code to enter the token. You need to copy the value of the "JWT_TOKEN" from the .env file created by the npm run generate-token command.

[!NOTE] In a real world scenario, you would want to validate the token and use a more secure method of authentication. This is just a demo token for testing purposes. Learn more about to secure your server here.

Option 2 - Manually Adding MCP Server to VS Code

1. Add MCP Server from command palette and add URL to your running server's HTTP endpoint:

For local development, the URL will be:

http://localhost:3000/mcp

For Azure Container Apps, the URL will be:

https://<env-name>.<container-id>.<region>.azurecontainerapps.io/mcp

1. Select HTTP (HTTP or Server-Sent Events) for the type of MCP server to add.
2. Enter the URL to your running HTTP endpoint, including the /mcp path at the end.
3. Enter the server ID. (This can be any name you want)
4. Choose if you want to run this in your User settings (available to all apps for you) or to your Workspace settings (available to this app, only)
5. In Copilot chat agent mode enter a prompt to trigger the tool, e.g., select some code and enter this prompt

I need to send an email to Dan, please add that to my todo list.

7. When prompted to run the tool, consent by clicking Continue,
8. When you're done, press Ctrl+C in the terminal window to stop the func.exe host process, and List MCP Servers from command palette and stop the local server.

Option 3 - MCP Inspector

1. In a new terminal window, install and run MCP Inspector

npm run inspect

1. CTRL click to load the MCP Inspector web app from the URL displayed in the terminal (e.g. http://localhost:6274/?MCP_PROXY_AUTH_TOKEN=xyz)
2. Set the transport type to Streamable HTTP.
3. Add authentication header: Authorization and Bearer token which is the value of the "JWT_TOKEN" from the .env file created by the npm run generate-token command.
4. Set the URL to your running server's HTTP endpoint and Connect:

# for local development, use:
http://localhost:3000/mcp

# or use the Azure Container Apps URL:
https://<env-name>.<container-id>.<region>.azurecontainerapps.io/mcp

5. List Tools. Click on a tool and Run Tool.

Next Steps

• Learn more about Model Context Protocol
• Learn more about Azure Container Apps
• Learn more about Azure AI Foundry
• Learn more about related MCP efforts from Microsoft

Join the Community

We encourage you to join our Azure AI Foundry Developer Community​ to share your experiences, ask questions, and get support:

• aka.ms/foundry/discord​ - Join our Discord community for real-time discussions and support.
• aka.ms/foundry/forum - Visit our Azure AI Foundry Developer Forum to ask questions and share your knowledge.