Practical Implementation

How to Build, Test, and Deploy MCP Apps with Real Tools and Workflows

(Click the image above to view video of this lesson)

Practical implementation is where the power of the Model Context Protocol (MCP) becomes tangible. While understanding the theory and architecture behind MCP is important, the real value emerges when you apply these concepts to build, test, and deploy solutions that solve real-world problems. This chapter bridges the gap between conceptual knowledge and hands-on development, guiding you through the process of bringing MCP-based applications to life.

Whether you are developing intelligent assistants, integrating AI into business workflows, or building custom tools for data processing, MCP provides a flexible foundation. Its language-agnostic design and official SDKs for popular programming languages make it accessible to a wide range of developers. By leveraging these SDKs, you can quickly prototype, iterate, and scale your solutions across different platforms and environments.

In the following sections, you’ll find practical examples, sample code, and deployment strategies that demonstrate how to implement MCP in C#, Java with Spring, TypeScript, JavaScript, and Python. You’ll also learn how to debug and test your MCP servers, manage APIs, and deploy solutions to the cloud using Azure. These hands-on resources are designed to accelerate your learning and help you confidently build robust, production-ready MCP applications.

Overview

This lesson focuses on practical aspects of MCP implementation across multiple programming languages. We’ll explore how to use MCP SDKs in C#, Java with Spring, TypeScript, JavaScript, and Python to build robust applications, debug and test MCP servers, and create reusable resources, prompts, and tools.

Learning Objectives

By the end of this lesson, you will be able to:

  • Implement MCP solutions using official SDKs in various programming languages
  • Debug and test MCP servers systematically
  • Create and use server features (Resources, Prompts, and Tools)
  • Design effective MCP workflows for complex tasks
  • Optimize MCP implementations for performance and reliability

Official SDK Resources

The Model Context Protocol offers official SDKs for multiple languages:

Working with MCP SDKs

This section provides practical examples of implementing MCP across multiple programming languages. You can find sample code in the samples directory organized by language.

Available Samples

The repository includes sample implementations in the following languages:

Each sample demonstrates key MCP concepts and implementation patterns for that specific language and ecosystem.

Core Server Features

MCP servers can implement any combination of these features:

Resources

Resources provide context and data for the user or AI model to use:

  • Document repositories
  • Knowledge bases
  • Structured data sources
  • File systems

Prompts

Prompts are templated messages and workflows for users:

  • Pre-defined conversation templates
  • Guided interaction patterns
  • Specialized dialogue structures

Tools

Tools are functions for the AI model to execute:

  • Data processing utilities
  • External API integrations
  • Computational capabilities
  • Search functionality

Sample Implementations: C# Implementation

The official C# SDK repository contains several sample implementations demonstrating different aspects of MCP:

  • Basic MCP Client: Simple example showing how to create an MCP client and call tools
  • Basic MCP Server: Minimal server implementation with basic tool registration
  • Advanced MCP Server: Full-featured server with tool registration, authentication, and error handling
  • ASP.NET Integration: Examples demonstrating integration with ASP.NET Core
  • Tool Implementation Patterns: Various patterns for implementing tools with different complexity levels

The MCP C# SDK is in preview and APIs may change. We will continuously update this blog as the SDK evolves.

Key Features

For complete C# implementation samples, visit the official C# SDK samples repository

Sample implementation: Java with Spring Implementation

The Java with Spring SDK offers robust MCP implementation options with enterprise-grade features.

Key Features

  • Spring Framework integration
  • Strong type safety
  • Reactive programming support
  • Comprehensive error handling

For a complete Java with Spring implementation sample, see Java with Spring sample in the samples directory.

Sample implementation: JavaScript Implementation

The JavaScript SDK provides a lightweight and flexible approach to MCP implementation.

Key Features

  • Node.js and browser support
  • Promise-based API
  • Easy integration with Express and other frameworks
  • WebSocket support for streaming

For a complete JavaScript implementation sample, see JavaScript sample in the samples directory.

Sample implementation: Python Implementation

The Python SDK offers a Pythonic approach to MCP implementation with excellent ML framework integrations.

Key Features

  • Async/await support with asyncio
  • FastAPI integration``
  • Simple tool registration
  • Native integration with popular ML libraries

For a complete Python implementation sample, see Python sample in the samples directory.

API management

Azure API Management is a great answer to how we can secure MCP Servers. The idea is to put an Azure API Management instance in front of your MCP Server and let it handle features you’re likely to want like:

  • rate limiting
  • token management
  • monitoring
  • load balancing
  • security

Azure Sample

Here’s an Azure Sample doing exactly that, i.e creating an MCP Server and securing it with Azure API Management.

See how the authorization flow happens in below image:

APIM-MCP

In the preceding image, the following takes place:

  • Authentication/Authorization takes place using Microsoft Entra.
  • Azure API Management acts as a gateway and uses policies to direct and manage traffic.
  • Azure Monitor logs all request for further analysis.

Authorization flow

Let’s have a look at the authorization flow more in detail:

Sequence Diagram

MCP authorization specification

Learn more about the MCP Authorization specification

Deploy Remote MCP Server to Azure

Let’s see if we can deploy the sample we mentioned earlier:

  1. Clone the repo

    git clone https://github.com/Azure-Samples/remote-mcp-apim-functions-python.git
cd remote-mcp-apim-functions-python

  2. Register Microsoft.App resource provider.

    • If you are using Azure CLI, run az provider register --namespace Microsoft.App --wait.
    • If you are using Azure PowerShell, run Register-AzResourceProvider -ProviderNamespace Microsoft.App. Then run (Get-AzResourceProvider -ProviderNamespace Microsoft.App).RegistrationState after some time to check if the registration is complete.

  3. Run this azd command to provision the api management service, function app(with code) and all other required Azure resources

    azd up

    This commands should deploy all the cloud resources on Azure

Testing your server with MCP Inspector

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

    npx @modelcontextprotocol/inspector

    You should see an interface similar to:

    Connect to Node inspector

  2. CTRL click to load the MCP Inspector web app from the URL displayed by the app (e.g. http://127.0.0.1:6274/#resources)

  3. Set the transport type to SSE

  4. Set the URL to your running API Management SSE endpoint displayed after azd up and Connect:

    https://<apim-servicename-from-azd-output>.azure-api.net/mcp/sse

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

If all the steps have worked, you should now be connected to the MCP server and you’ve been able to call a tool.

MCP servers for Azure

Remote-mcp-functions: This set of repositories are quickstart template for building and deploying custom remote MCP (Model Context Protocol) servers using Azure Functions with Python, C# .NET or Node/TypeScript.

The Samples provides a complete solution that allows developers to:

  • Build and run locally: Develop and debug a MCP server on a local machine
  • Deploy to Azure: Easily deploy to the cloud with a simple azd up command
  • Connect from clients: Connect to the MCP server from various clients including VS Code’s Copilot agent mode and the MCP Inspector tool

Key Features

  • Security by design: The MCP server is secured using keys and HTTPS
  • Authentication options: Supports OAuth using built-in auth and/or API Management
  • Network isolation: Allows network isolation using Azure Virtual Networks (VNET)
  • Serverless architecture: Leverages Azure Functions for scalable, event-driven execution
  • Local development: Comprehensive local development and debugging support
  • Simple deployment: Streamlined deployment process to Azure

The repository includes all necessary configuration files, source code, and infrastructure definitions to quickly get started with a production-ready MCP server implementation.

Key Takeaways

  • MCP SDKs provide language-specific tools for implementing robust MCP solutions
  • The debugging and testing process is critical for reliable MCP applications
  • Reusable prompt templates enable consistent AI interactions
  • Well-designed workflows can orchestrate complex tasks using multiple tools
  • Implementing MCP solutions requires consideration of security, performance, and error handling

Exercise

Design a practical MCP workflow that addresses a real-world problem in your domain:

  1. Identify 3-4 tools that would be useful for solving this problem
  2. Create a workflow diagram showing how these tools interact
  3. Implement a basic version of one of the tools using your preferred language
  4. Create a prompt template that would help the model effectively use your tool

Additional Resources

Next: Advanced Topics