What You Will Learn

In this article, you will learn:

• What AI agents are.
• How agents use tools.
• What MCP is.
• How agents interact with enterprise systems.
• What safety controls agents need.

Introduction

An AI agent is an AI-powered workflow that can reason about a goal, choose steps, use tools, and produce a result.

A normal chatbot answers a prompt.

An agent may:

• Understand the task.
• Plan steps.
• Search documents.
• Call tools.
• Validate results.
• Ask for clarification.
• Complete a workflow.

Agent Flow

flowchart TD
    A["User goal"] --> B["Agent"]
    B --> C["Plan"]
    C --> D["Choose tool"]
    D --> E["Execute tool in application"]
    E --> F["Observe result"]
    F --> G["Continue or finish"]

What Tools Mean

Tools are functions the application exposes to the AI system.

Examples:

• Search customer orders.
• Create a support ticket.
• Query a database.
• Retrieve a document.
• Send an approval request.

The model decides that a tool is needed, but the application should execute the tool safely.

Agent vs Workflow

Workflow	Agent
Fixed steps	Dynamic steps
Predictable path	Can choose tools
Easier to test	More flexible
Lower autonomy	Higher autonomy

Many production systems combine both: deterministic workflows for critical actions and agents for flexible reasoning.

What Is MCP?

MCP stands for Model Context Protocol.

MCP is a protocol that standardizes how AI applications connect to tools, resources, and external systems.

It helps AI clients discover and use capabilities exposed by servers.

MCP Concepts

Concept	Meaning
MCP client	AI application that connects to MCP servers
MCP server	Service exposing tools or resources
Tool	Callable operation
Resource	Data the AI client can read
Prompt	Reusable instruction template

MCP Flow

flowchart LR
    A["AI application"] --> B["MCP client"]
    B --> C["MCP server"]
    C --> D["Tools and resources"]
    D --> C
    C --> B
    B --> A

Enterprise Agent Use Cases

• Customer support resolution.
• Incident investigation.
• Developer productivity assistants.
• Policy lookup and summarization.
• Data analysis assistants.
• Workflow triage and routing.

Safety Controls

Agents need strong controls:

• Authentication.
• Authorization.
• Tool allowlists.
• Human approval for risky actions.
• Audit logs.
• Rate limits.
• Output validation.
• Clear rollback strategy.

Interview Questions

What is an AI agent?

An AI agent is a system that uses an AI model to plan, choose tools, observe results, and complete a goal.

What is MCP?

MCP is a protocol for connecting AI applications to tools, resources, and external systems in a standard way.

Should AI models directly execute business actions?

No. The application should own authorization, validation, execution, and auditing.

Summary

AI agents extend LLM applications from answering questions to completing workflows. MCP helps standardize tool and resource integration, but production agents still need strict safety and governance.