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Creating Custom AI Agents
Creating Custom AI Agents
Introduction to Model Context Protocol
The Model Context Protocol (MCP) is a flexible communication framework that allows software components clients, servers, and services to exchange data in a structured, context-aware way.
Model Context Protocol (MCP) is designed to manage context and data flow between AI models and external tools or services, using a consistent data model. When building your own AI agent, you don’t need to start from scratch just define its behavior, required context, and the services it should interact with. MCP handles the structure and logic that make everything work together.
Context-aware communication;
Routing between inputs, services, and responses;
Easy integration with tools like Excel or APIs;
Optional AI processing via models like Claude or GPT.
MCP lets you focus on your agent's on logic while it manages the connections and ensuring everything will work when you connect AI to it.
You can write functions to perform specific tasks using local data, local apps, or online services. If you're using Excel and often analyze product performance, you might create a function like get_top_products_by_revenue. Using MCP, you can set up a connection to the AI, allowing it to call this function automatically when needed
The AI, using its context-awareness, will understand your request, call the appropriate function, fetch the necessary data, execute the function, and return the result automatically.
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