Building MCP Servers in .NET for AI Agents, a 10-part tutorial series

Taiseer Joudeh — Fri, 06 Nov 2026 11:42:10 +0000

If you're a .NET developer and you want to build an MCP server, it's hard to know where to start. Most examples stop at a "hello world" tool running on your own machine. I wanted a series that goes from that first tool all the way to a server that real users can sign in to and use from different AI clients.

So I wrote one. It's 10 parts, it's free, and it's built on .NET 10 and ASP.NET Core from start to finish.

What you'll build

The whole series builds one sample app, BitOfTech Expenses, an MCP server for expense reports and approvals. Each part adds to the one before it, so by the end you have a complete, working server and not a set of separate demos.

By the end of the series, you'll have:

A working MCP server in C# with tools, resources and prompts, connected to a real database and an external API.
The server hosted in ASP.NET Core and secured with Microsoft Entra ID, so each user only sees and runs the tools they're allowed to use.
A deployment on Azure Container Apps that you can use from VS Code Copilot, Claude, your own .NET agent and Microsoft Foundry.
A clear view of what it costs to run and how to protect it from common MCP security risks.

The 10 parts

Who it's for

The series is for .NET developers who know C# and ASP.NET Core but are new to MCP. You don't need any AI or machine learning background. If you can build a Minimal API, you can follow along.

What you need

The .NET 10 SDK and VS Code.
Parts 1 to 3 run on your own machine, with no cloud account.
From Part 4 onwards, you need an Azure subscription.

Source code

Everything is on GitHub, with a git tag for each part. If you get stuck, you can check out the tag for the part you're on and compare it with your code.

🔗 https://github.com/tjoudeh/building-mcp-servers-dotnet

I verified every step before publishing, but MCP and its tooling change quickly. If something doesn't work for you, leave a comment here or open an issue on the repo, and I'll take a look.

Practical Azure Container Apps with Dapr

Taiseer Joudeh — Mon, 26 Sep 2022 09:20:24 +0000

This post is originally posted at medium.com

Azure Container Apps is a fully managed serverless container runtime for building and running cloud-native applications which focuses on the business logic of the apps rather than on cloud infrastructure management.

Azure Container Apps is built upon the foundation consisting of open-source technology with CNCF projects like Kubernetes Event-Driven Autoscaling (KEDA), Distributed Application Runtime (Dapr), and Envoy running on the Azure Kubernetes Service (AKS).

During the past month, I spent quite a time digging deeper and learning more about this serverless offering.

Theoretical learning is great, but nothing beats a practical example! So I've created a simple microservice application (Tasks Management App) which consists of three microservices and each one has certain capabilities to show how Azure Container Apps and Dapr can simplify the building of a microservices application.

Complete practical example on my blog. The source code is available on GitHub.

The below architecture diagram shows the solution components and services I'm using in this practical example

To help understand how I build the application from scratch, I have written various companion blog posts to describe the source code and walk you through the steps.

The application use cases and Azure Container Apps features I will be covered are below:

An overview of Azure Container Apps Components and Dapr and their core features and capabilities (continue reading…)
Getting started with Azure Container Apps, build and push container image to Azure Container Registry, then deploy your first Backend API microservice (continue reading…)
Communication between two microservices (without Dapr) and different options for ingress configurations (continue reading…)
Introducing Dapr into the application and how it will help simplify complex microservices scenarios such as service discovery, service-to-service invocation, and calling services asynchronously (continue reading…)
Enable local debugging for multiple microservices applications within VS Code and configure Dapr locally (continue reading…)
Using Dapr State Management Building Block to store application data into Azure Cosmos DB with simple configurations and without adding CosmosDB SDK to the application (continue reading…)
Using Dapr Pub/Sub Building Block to enable Async communication between microservices while using Azure Service Bus as a service broker, and see how Dapr will simplify the process on the producer and consumer too (continue reading…)
Handling external events from different systems and showing the connectivity and interoperability capabilities when introducing Dapr Bindings (continue reading…)
Introducing Cron binding to trigger application code periodically based on a configurable interval and store processing results Azure Blob Storage using Dapr State Management API (continue reading…)
Configure Monitoring and Observability for all applications in the Azure Container App Environment and implement distributed tracing between services and resources using Application Insights (continue reading…)
Use GitHub actions to continuously build, push images to ACR and deploy new Azure Container Apps revisions with code changes (continue reading…)
Creating the IaC scripts to recreate the entire ACA environment with the supporting resources (Azure Service Bus, Cosmos DB, Azure storage, etc…) using Bicep (continue reading…)
Configuring Autoscaling for Azure Container Apps using KEDA based on Azure Service Bus Queue length (continue reading…)
Integrating Health probes in Azure Container Apps (TBA)

I will be adding more posts such as Authentication, services invocation using gRPC, file storage mounting, and using vNETs during the coming period, so stay tuned and thanks for reading.

Happy learning and coding!

References:

Featured Image Credit

DEV Community: Taiseer Joudeh