The Model Context Protocol: A Universal Interface for AI Native Development

The Transformative Power of the Model Context Protocol (MCP)

In a dynamic and enlightening session, Doug Finke, a 16-time Microsoft MVP, delved into the Model Context Protocol (MCP) and its pivotal role in AI-driven development. His presentation highlighted the vast potential of MCP as a universal interface connecting AI models to tools and data, transforming how developers interact with AI technology. Finke's passion for the evolution of AI was palpable as he shared, “I’ve been playing with AI since the ‘80s,” framing MCP as a significant leap forward in AI technology.

Hands-On Demonstrations: MCP in Action

Finke’s deep dive into MCP included practical demonstrations using Visual Studio Code, Python, and GitHub Copilot, showcasing the ease with which developers can integrate MCP into their workflows. He emphasized the simplicity of the process: “You’re just basically using standard code that you’re used to.” By using a Python function and an MCP decorator, he illustrated how AI tools can be accessed without the usual complexities of SDKs or plugins. This hands-on approach provided clear evidence of MCP's capability to streamline AI-native development, making it accessible and efficient.

The Agentic Advantage: Enhancing AI Reliability

One of the standout features of MCP discussed was its ability to enhance AI reliability through what Finke described as “agentic tool use.” He noted, “Claude sonnet hallucinated the calculation result. That’s the reason why we use agents and we give it tools right—so that it can actually say, ‘Oh, I have to do a multiplication… I’m not good at that, but I’m going to use a tool for it.’” This approach not only improves the accuracy of AI computations but also ensures operational safety by leveraging external tools for complex tasks.

Universality and Historical Parallels

Finke positioned MCP as an "open protocol for connecting AI models to tools and to data," emphasizing its universality. He drew historical parallels to the Java pitch of "write once, run everywhere," but clarified that MCP is about unifying tool interactions rather than code execution locations. This universality, he argued, is crucial for consistent and reliable AI applications across various environments and developer mindsets.

Practical Use Cases and Security Concerns

Finke explored various use cases for MCP, from enhancing AI coding assistants to integrating enterprise workflows with tools like JIRA and Confluence. He also addressed security and governance, emphasizing “host-mediated permissions” and “auditing.” This focus reassured developers that while MCP facilitates powerful AI capabilities, it also aligns with best practices in security and responsible adoption.

Looking Forward: MCP’s Rapid Adoption and Potential

Concluding his talk, Finke highlighted the rapid adoption of MCP and its potential to spark developer creativity. He encouraged attendees to experiment and innovate, stating, “It’s just code—and it has access to an LLM. They’re just making it easier so you can get your job done.” This enthusiasm underscored MCP's role as a catalyst for the next wave of AI development.

About The Speaker

Doug Finke

Doug Finke is a 16-time Microsoft MVP, creator of the ImportExcel and PSAI modules, and an early pioneer of AI inside the shell. He’s spent years automating everything from mainframes to GitHub Copilot and now livestreams "The AI Build Hour," helping developers ship faster with agent-driven tooling.