Content
<!--
---
name: Remote MCP with Azure Functions (Python)
description: Run a remote MCP server on Azure functions.
page_type: sample
languages:
- python
- bicep
- azdeveloper
products:
- azure-functions
- azure
urlFragment: remote-mcp-functions-python
---
-->
# Getting Started with Remote MCP Servers using Azure Functions (Python)
This is a quickstart template to easily build and deploy a custom remote MCP server to the cloud using Azure Functions with Python. You can clone/restore/run on your local machine with debugging, and `azd up` to have it in the cloud in a couple minutes. The MCP server is secured by design using keys and HTTPS, and allows more options for OAuth using built-in auth and/or API Management as well as network isolation using VNET.
If you're looking for this sample in more languages check out the [.NET/C#](https://github.com/Azure-Samples/remote-mcp-functions-dotnet) and [Node.js/TypeScript](https://github.com/Azure-Samples/remote-mcp-functions-typescript) versions.
[](https://codespaces.new/Azure-Samples/remote-mcp-functions-python)
Below is the architecture diagram for the Remote MCP Server using Azure Functions:
## Prerequisites
+ [Python](https://www.python.org/downloads/) version 3.11 or higher
+ [Azure Functions Core Tools](https://learn.microsoft.com/azure/azure-functions/functions-run-local?pivots=programming-language-python#install-the-azure-functions-core-tools)
+ [Azure Developer CLI](https://aka.ms/azd)
+ To use Visual Studio Code to run and debug locally:
+ [Visual Studio Code](https://code.visualstudio.com/)
+ [Azure Functions extension](https://marketplace.visualstudio.com/items?itemName=ms-azuretools.vscode-azurefunctions)
## Prepare your local environment
An Azure Storage Emulator is needed for this particular sample because we will save and get snippets from blob storage.
1. Start Azurite
```shell
docker run -p 10000:10000 -p 10001:10001 -p 10002:10002 \
mcr.microsoft.com/azure-storage/azurite
```
>**Note** if you use Azurite coming from VS Code extension you need to run `Azurite: Start` now or you will see errors.
## Run your MCP Server locally from the terminal
1. Change to the src folder in a new terminal window:
```shell
cd src
```
1. Install Python dependencies:
```shell
pip install -r requirements.txt
```
1. Start the Functions host locally:
```shell
func start
```
> **Note** by default this will use the webhooks route: `/runtime/webhooks/mcp/sse`. Later we will use this in Azure to set the key on client/host calls: `/runtime/webhooks/mcp/sse?code=<system_key>`
## Use the MCP server from within a client/host
### VS Code - Copilot Edits
1. **Add MCP Server** from command palette and add URL to your running Function app's SSE endpoint:
```shell
http://0.0.0.0:7071/runtime/webhooks/mcp/sse
```
1. **List MCP Servers** from command palette and start the server
1. In Copilot chat agent mode enter a prompt to trigger the tool, e.g., select some code and enter this prompt
```plaintext
Say Hello
```
```plaintext
Save this snippet as snippet1
```
```plaintext
Retrieve snippet1 and apply to newFile.py
```
1. When prompted to run the tool, consent by clicking **Continue**
1. When you're done, press Ctrl+C in the terminal window to stop the Functions host process.
### MCP Inspector
1. In a **new terminal window**, install and run MCP Inspector
```shell
npx @modelcontextprotocol/inspector
```
2. CTRL click to load the MCP Inspector web app from the URL displayed by the app (e.g. http://0.0.0.0:5173/#resources)
3. Set the transport type to `SSE`
4. Set the URL to your running Function app's SSE endpoint and **Connect**:
```shell
http://0.0.0.0:7071/runtime/webhooks/mcp/sse
```
5. **List Tools**. Click on a tool and **Run Tool**.
## Deploy to Azure for Remote MCP
Run this [azd](https://aka.ms/azd) command to provision the function app, with any required Azure resources, and deploy your code:
```shell
azd up
```
You can opt-in to a VNet being used in the sample. To do so, do this before `azd up`
```bash
azd env set VNET_ENABLED true
```
Additionally, [API Management]() can be used for improved security and policies over your MCP Server, and [App Service built-in authentication](https://learn.microsoft.com/azure/app-service/overview-authentication-authorization) can be used to set up your favorite OAuth provider including Entra.
### Connect to your function app from a client
Your client will need a key in order to invoke the new hosted SSE endpoint, which will be of the form `https://<funcappname>.azurewebsites.net/runtime/webhooks/mcp/sse`. The hosted function requires a system key by default which can be obtained from the [portal](https://learn.microsoft.com/azure/azure-functions/function-keys-how-to?tabs=azure-portal) or the CLI (`az functionapp keys list --resource-group <resource_group> --name <function_app_name>`). Obtain the system key named `mcp_extension`.
For MCP Inspector, you can include the key in the URL: `https://<funcappname>.azurewebsites.net/runtime/webhooks/mcp/sse?code=<your-mcp-extension-system-key>`.
For GitHub Copilot within VS Code, you should instead set the key as the `x-functions-key` header in `mcp.json`, and you would just use `https://<funcappname>.azurewebsites.net/runtime/webhooks/mcp/sse` for the URL. The following example uses an input and will prompt you to provide the key when you start the server from VS Code:
```json
{
"inputs": [
{
"type": "promptString",
"id": "functions-mcp-extension-system-key",
"description": "Azure Functions MCP Extension System Key",
"password": true
}
],
"servers": {
"my-mcp-server": {
"type": "sse",
"url": "<funcappname>.azurewebsites.net/runtime/webhooks/mcp/sse",
"headers": {
"x-functions-key": "${input:functions-mcp-extension-system-key}"
}
}
}
}
```
## Redeploy your code
You can run the `azd up` command as many times as you need to both provision your Azure resources and deploy code updates to your function app.
>[!NOTE]
>Deployed code files are always overwritten by the latest deployment package.
## Clean up resources
When you're done working with your function app and related resources, you can use this command to delete the function app and its related resources from Azure and avoid incurring any further costs:
```shell
azd down
```
## Helpful Azure Commands
Once your application is deployed, you can use these commands to manage and monitor your application:
```bash
# Get your function app name from the environment file
FUNCTION_APP_NAME=$(cat .azure/$(cat .azure/config.json | jq -r '.defaultEnvironment')/env.json | jq -r '.FUNCTION_APP_NAME')
echo $FUNCTION_APP_NAME
# Get resource group
RESOURCE_GROUP=$(cat .azure/$(cat .azure/config.json | jq -r '.defaultEnvironment')/env.json | jq -r '.AZURE_RESOURCE_GROUP')
echo $RESOURCE_GROUP
# View function app logs
az webapp log tail --name $FUNCTION_APP_NAME --resource-group $RESOURCE_GROUP
# Redeploy the application without provisioning new resources
azd deploy
```
## Source Code
The function code for the `get_snippet` and `save_snippet` endpoints are defined in the Python files in the `src` directory. The MCP function annotations expose these functions as MCP Server tools.
Here's the actual code from the function_app.py file:
```python
@app.generic_trigger(arg_name="context", type="mcpToolTrigger", toolName="hello",
description="Hello world.",
toolProperties="[]")
def hello_mcp(context) -> None:
"""
A simple function that returns a greeting message.
Args:
context: The trigger context (not used in this function).
Returns:
str: A greeting message.
"""
return "Hello I am MCPTool!"
@app.generic_trigger(
arg_name="context",
type="mcpToolTrigger",
toolName="getsnippet",
description="Retrieve a snippet by name.",
toolProperties=tool_properties_get_snippets_json
)
@app.generic_input_binding(
arg_name="file",
type="blob",
connection="AzureWebJobsStorage",
path=_BLOB_PATH
)
def get_snippet(file: func.InputStream, context) -> str:
"""
Retrieves a snippet by name from Azure Blob Storage.
Args:
file (func.InputStream): The input binding to read the snippet from Azure Blob Storage.
context: The trigger context containing the input arguments.
Returns:
str: The content of the snippet or an error message.
"""
snippet_content = file.read().decode("utf-8")
logging.info(f"Retrieved snippet: {snippet_content}")
return snippet_content
@app.generic_trigger(
arg_name="context",
type="mcpToolTrigger",
toolName="savesnippet",
description="Save a snippet with a name.",
toolProperties=tool_properties_save_snippets_json
)
@app.generic_output_binding(
arg_name="file",
type="blob",
connection="AzureWebJobsStorage",
path=_BLOB_PATH
)
def save_snippet(file: func.Out[str], context) -> str:
content = json.loads(context)
snippet_name_from_args = content["arguments"][_SNIPPET_NAME_PROPERTY_NAME]
snippet_content_from_args = content["arguments"][_SNIPPET_PROPERTY_NAME]
if not snippet_name_from_args:
return "No snippet name provided"
if not snippet_content_from_args:
return "No snippet content provided"
file.set(snippet_content_from_args)
logging.info(f"Saved snippet: {snippet_content_from_args}")
return f"Snippet '{snippet_content_from_args}' saved successfully"
```
Note that the `host.json` file also includes a reference to the experimental bundle, which is required for apps using this feature:
```json
"extensionBundle": {
"id": "Microsoft.Azure.Functions.ExtensionBundle.Experimental",
"version": "[4.*, 5.0.0)"
}
```
## Next Steps
- Add [API Management]() to your MCP server
- Add [built-in auth]() to your MCP server
- Enable VNET using VNET_ENABLED=true flag
- Learn more about [related MCP efforts from Microsoft]()
