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Agentic AI for Automating Daily Office Tasks with Anthropic Claude

bookWhat is Agentic AI?

Note
Definition

Agentic AI refers to autonomous artificial intelligence systems that independently plan tasks, make decisions, and use digital tools to achieve specific goals. Unlike traditional chatbots, these AI agents can manage emails, coordinate meetings, execute workflows across multiple applications, and adapt to changing environments without constant human supervision.

Note
Definition

The Model Context Protocol (MCP) serves as the crucial infrastructure that enables agentic AI to function effectively in real-world business environments. MCP acts as a standardized communication layer between AI models and external tools.

MCP Architecture Components

  • Language model layer: this includes foundation models like Claude, GPT-4, or LLaMA that provide the core reasoning and natural language processing capabilities;
  • Protocol layer: MCP itself, which manages communication, context preservation, and execution logic between the model and external services;
  • Tool integration layer: the various applications and services that the AI can interact with.
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SectionΒ 1. ChapterΒ 1

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bookWhat is Agentic AI?

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Note
Definition

Agentic AI refers to autonomous artificial intelligence systems that independently plan tasks, make decisions, and use digital tools to achieve specific goals. Unlike traditional chatbots, these AI agents can manage emails, coordinate meetings, execute workflows across multiple applications, and adapt to changing environments without constant human supervision.

Note
Definition

The Model Context Protocol (MCP) serves as the crucial infrastructure that enables agentic AI to function effectively in real-world business environments. MCP acts as a standardized communication layer between AI models and external tools.

MCP Architecture Components

  • Language model layer: this includes foundation models like Claude, GPT-4, or LLaMA that provide the core reasoning and natural language processing capabilities;
  • Protocol layer: MCP itself, which manages communication, context preservation, and execution logic between the model and external services;
  • Tool integration layer: the various applications and services that the AI can interact with.
Everything was clear?

How can we improve it?

Thanks for your feedback!

SectionΒ 1. ChapterΒ 1
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