MCP for Developers: Build AI Tools & Servers with C#

About this course

Everyone can now explain what Model Context Protocol is. Almost nobody can ship a server that a team would trust in production. This course is the second half of that sentence. From lecture three onward you are in Visual Studio writing C#, and by the end you have a hardened, containerised, deployed MCP server that an AI client uses to investigate real production failures. You work on one running system for the whole course. Nebula Arena is a live-ops game backend you inherit: a Postgres database of players, sessions, items and error logs, a GitHub repository, and a .NET codebase with real problems in it. Against that system you build DevAssist, an MCP server that gives an AI client safe, governed access to all three surfaces. By the final section you hand Claude Code the sentence "investigate why player authentication is failing" and watch it chain five of your tools to a root cause. What you will build and learn: Write MCP servers in C# with the official MCP SDK for .NET, from empty project to running tool call Design tools the model actually calls correctly: naming, descriptions, input validation, structured output, blast radius Expose resources and prompts, not just tools, and know when each one is the right primitive Query Postgres and wrap the GitHub REST API behind tools that cannot be abused Connect your server to Claude Code and Claude Desktop, and see exactly how a model turns intent into arguments into a call Secure it properly: trust boundaries, secrets, least privilege, why a generic execute_sql tool is a loaded gun, and how to blunt prompt injection arriving through tool results Choose stateful or stateless deliberately, then containerise and deploy to AWS with ECS, an ALB and RDS Build a codebase server with search_code, get_file, Roslyn-powered find_symbol and dependency analysis Handle production reality: timeouts, retries,

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