AI and Your Data: Making Sense of the Jargon
Hey everyone, John here! Today, we’re diving into something called the Model Context Protocol, or MCP. Sounds complicated, right? Don’t worry, we’ll break it down nice and easy. The main idea is this: how do we get those super-smart AI programs (like the ones that write stories or answer questions) to use YOUR information, not just the stuff they learned from the internet?
You see, these AI programs, often called Large Language Models (LLMs), are like really smart students. They’ve read tons of books and websites. But if you want them to help with *your* specific data – like your company’s sales reports or your personal notes – they need a way to “understand” it. That’s where MCP comes in!
Lila, our AI newbie, has a question, I’m sure:
Lila: “John, what exactly IS an LLM?”
John: “Great question, Lila! An LLM is like a super-powered parrot that can understand and generate human language. Think of it as a very advanced chatbot. It’s been trained on a massive amount of text data to understand patterns and relationships in language, allowing it to answer questions, write stories, translate languages, and much more.”
MCP: The AI “USB Port”
The Model Context Protocol is a way to connect these smart AI programs with your specific data. Think of it like a universal adapter – a “USB-C port for AI applications,” as the developers put it. It allows the AI to “plug into” your data, understand it, and give you useful answers. Without it, an AI might give you generic answers that aren’t helpful for your specific needs.
Why is this important?
- Accuracy: It helps the AI give you accurate answers based on your information.
- Relevance: It makes sure the AI understands your specific business, personal context, or project.
- Control: You get to decide what data the AI has access to.
MCP in Action: Using Azure
The article focuses on how Microsoft is using MCP within its Azure cloud platform. Azure is like a giant set of tools and services that companies and individuals use to build websites, store data, and run software. Microsoft has built tools to help you connect AI to your data in Azure.
The Azure MCP Server
One of the key tools is the Azure MCP Server. It’s like a translator, taking requests from AI programs and getting them the information they need from Azure. This server is open source, meaning anyone can use it and even make changes to it. It connects to lots of different Azure services, like databases and storage, so the AI can access the data stored there.
Lila: “So, the MCP Server lets the AI talk to all these different parts of Azure?”
John: “Exactly, Lila! It’s like the AI has a super-smart assistant that can fetch information from all over Azure and bring it back in a way the AI can understand.”
Using MCP with GitHub Copilot
You can even use the Azure MCP Server with tools like GitHub Copilot, which is an AI assistant for writing code. This means you can ask Copilot questions about your Azure setup, like “List my Azure subscriptions.” The MCP Server then gets the answer from Azure and gives it to Copilot. It’s like having a chat with your Azure account!
This is a good way to learn MCP, using an environment you might already be using.
MCP and Azure AI Foundry
Microsoft is also using MCP in a platform called Azure AI Foundry. This is where they build and test AI applications. This integration allows you to easily connect different AI tools and data sources, making it easier to build and deploy AI solutions.
The article also mentioned “agents”. Think of an agent as an AI assistant that can perform specific tasks. For instance, you might have an agent that creates the infrastructure needed on Azure, or an agent that answers questions about your company’s financials.
MCP and Semantic Kernel
Finally, Microsoft is working to integrate MCP with Semantic Kernel, another tool that helps you build AI applications. This will allow you to create powerful AI agents that can access and use a wide variety of information sources.
Basically, MCP is helping integrate tools to make AI better, easier to use, and much more useful for your specific needs.
My Thoughts
This whole MCP thing seems pretty cool. It’s about connecting AI to the real world, making it actually useful for real-world problems. It’s the next step to making the large language models useful for your business!
Lila: “Wow, John! That actually makes a lot of sense. So, instead of just being able to write poems, AI can actually help me with my job! That’s super exciting!”
John: “Exactly, Lila! It’s a whole new world of possibilities!”
This article is based on the following original source, summarized from the author’s perspective:
Using the Model Context Protocol in Azure and beyond