This tag archive covers the Model Context Protocol, a critical component in successful agentic AI implementations, which involves contextualizing models to accurately interpret and react to user input. Effective use of this protocol is crucial for software engineers working with AI, as it directly impacts the reliability and usability of such systems.
3 articles since Sep 2026
Learn how to design, test, and operate MCP server versioning and backward compatibility at scale, with concrete patterns, CI/CD pipelines, and real‑world case studies.
Explore the anatomy of MCP server architecture, from Model Context Protocol fundamentals to .NET tooling, Azure integration, and production‑grade prompt engineering.
Explore how MCP Server and Azure OpenAI function calling reshape .NET AI integrations, from latency and state handling to multi‑agent orchestration and cost optimization.