all Technical posts
Once your MCP server is ready, it needs a place to live where your AI applications can talk to it. In this blog post, we'll explore how to deploy an MCP server reliably and securely—from local development to production—so the connection between your host application and your MCP server stays stable and your AI workflows continue running without interruption.
all Technical posts
Once you've built your own MCP server, the interesting part comes: how to use it effectively in your AI-driven applications? In this blog post, we'll explore how to connect, test, and deploy your server so AI agents can truly collaborate with your tools and data.
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Unlocking the Value of Dynamics 365 Through Integration
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Build your own MCP server in .NET
As MCP is increasingly used to connect AI to real-world systems, the need for concrete examples is growing. What does this mean for you as a .NET developer? In this post, we'll walk you through building your own MCP server in .NET, so you can securely share tools, workflows, and data with AI systems like ChatGPT or Copilot.
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AI is evolving fast—but to be truly useful, it needs a secure way to connect with your systems. That’s where the Model Context Protocol (MCP) comes in. Read on to discover how MCP bridges AI and your tools.