How AI Agents Actually Call APIs: 5 Common Misconceptions

Kong

Oct 10, 2025

Ever wondered how AI agents and Large Language Models (LLMs) connect to real-world data and services? It’s not magic—it’s a well-structured process. This video breaks down the five most common misunderstandings about how LLMs call APIs, databases, and other custom tools. We explain the crucial role of the Model Context Protocol (MCP) in creating reliable and powerful AI agents.

In this video, we'll cover:

Myth #1: The LLM runs on your laptop. We explain why the model almost always lives in the cloud on large GPU clusters.

Myth #2: The LLM magically knows how to use tools. An LLM needs instructions and schemas to understand what a tool can do and how to use it.

Myth #3: Tools live inside the LLM. Tools are external APIs or services; the LLM only generates a structured request to call them.

Myth #4: The LLM executes the tool itself. The model's job is to generate text; a separate runtime is responsible for executing the tool call.

Myth #5: Tool calls are always reliable. Learn how protocols like MCP help validate inputs, enforce contracts, and handle errors for more robust systems.

Understanding this process is key to building AI systems that are powerful and dependable, not fragile.