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Building Your First MCP Server with .NET and Publishing to NuGet

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Building Your First MCP Server with .NET and Publishing to NuGet

Learn how to create a Model Context Protocol (MCP) server using .NET 10, publish it to NuGet, and make your AI tools discoverable and reusable by the .NET community.

Creating Your First MCP Server

Explore the step-by-step process of building a simple MCP server that provides weather information and random numbers, leveraging the .NET 10 MCP templates.

Prerequisites

Make sure you have the necessary tools before getting started, including .NET 10.0 SDK, Visual Studio Code, GitHub Copilot extension, and a NuGet.org account.

Step 1: Install the MCP Template

Install the MCP Server template to begin creating your MCP server with the latest features and enhancements.

Step 2: Create Your MCP Server Project

Use the MCP template to set up your MCP server project and start building custom tools and configurations for AI assistance.

Adding Custom Tools and Configuration

Enhance your MCP server by adding a weather tool that utilizes environment variables for configuration, showcasing parameter acceptance and response generation.

Testing Your MCP Server

Configure GitHub Copilot to interact with your MCP server, and test its functionality with prompts related to weather information and random number generation.

Configuring for NuGet Publication

Update your project files to prepare for publishing your MCP server to NuGet, including declaring inputs, metadata, and a unique package ID.

Publishing to NuGet

Learn how to pack your project and publish it to NuGet, making your MCP server available for the broader .NET community to discover and utilize.

What’s Next?

Explore the possibilities of .NET 10 and NuGet for MCP servers, share your feedback, and stay engaged with the AI & .NET community for further developments and enhancements.

Resources

Access additional resources and documentation to deepen your understanding of .NET AI, the Model Context Protocol, and the NuGet ecosystem for building extensible AI tools and solutions.