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Aspire.MCP.Sample

by elbruno

UtilitiesAspireC#ServerClientAzure

This sample demonstrates a Model Context Protocol (MCP) Server and client setup using Aspire. It showcases how to establish and manage MCP communication, using C# in a structured Aspire environment.

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Aspire.MCP.Sample

Sample MCP Server and MCP client using Aspire.

Overview

This sample demonstrates a Model Context Protocol (MCP) Server and client setup using Aspire. It showcases how to establish and manage MCP communication, using C# in a structured Aspire environment.

Quick Demo

Check out this 5-minute video overview to see the project in action.

5-Minute Overview of the Project

5-Minute Overview of the Project

Check out this 5-minute video overview to see how to deploy the solution to Azure, and how to consume the deployed MCP Server in Azure from Visual Studio Code.

5-Minute Overview on how to deploy the solution to Azure

5-Minute Overview on how to deploy the solution to Azure

Features

  • Aspire Integration: Uses Aspire for containerized orchestration and service management.
  • MCP Server: Implements an MCP server to manage client communication.
  • MCP Client: Sample Blazor Chat client demonstrating how to connect and communicate with the MCP server.
  • Model Selection: The Chat Client can use LLMs from Azure AI Foundry, Ollama or GitHub models. The selected model must support function calling to be able to call the MCP server functions.
  • Function Calling: Demonstrates how to call functions from the MCP server using the selected model.
  • Tool Result: Displays the result of the function call in the chat interface.
  • Azure Deployment: The project can be easily deployed to Azure using azd commands.

Getting Started

Prerequisites

  • .NET SDK 9.0 or later
  • Visual Studio 2022 or Visual Studio code
  • LLM or SLM that supports function calling.
    • Azure AI Foundry to run models in the cloud. IE: gpt-4o-mini
    • GitHub Models to run models in the cloud. IE: gpt-4o-mini
    • Ollama for running local models. Suggested: phi4-mini, llama3.2 or Qwq

Run locally

  1. Clone the repository:

  2. Navigate to the Aspire project directory:

    cd .\src\McpSample.AppHost\

  3. Run the project:

    dotnet run

  4. In the Aspire Dashboard, navigate to the Blazor Chat client project.

    Aspire Dashboard

    Aspire Dashboard

  5. In the Chat Settings page, define the model to be used. You choose to use models in Azure AI Foundry (suggested gpt-4o-mini), GitHub Models or locally with ollama (suggested llama3.2)

    Chat Settings

    Chat Settings

  6. Now you can chat with the model. Everytime that one of the functions of the MCP server is called, the Tool Result section will be displayed in the chat.

    Chat Demo

    Chat Demo

Architecture Diagram

Architecture Diagram

Architecture Diagram

GitHub Codespaces

(WIP)

  • Codespaces configuration will be added soon.

Deployment

Once you've opened the project in Codespaces, or locally, you can deploy it to Azure.

From a Terminal window, open the folder with the clone of this repo and run the following commands.

  1. Login to Azure:

    azd auth login

  2. Provision and deploy all the resources:

    azd up

    It will prompt you to provide an azd environment name (like "aspiremcp"), select a subscription from your Azure account, and select a location.

  3. When azd has finished deploying, you'll see the list of resources created in Azure and a set of URIs in the command output.

  4. Visit the blazorchat URI, and you should see the MCP Chat App! 🎉

Note: The deploy files are located in the ./src/McpSample.AppHost/infra/ folder. They are generated by the Aspire AppHost project.

Contributing

Contributions are welcome! Feel free to submit issues and pull requests.

License

This project is licensed under the MIT License.