Glossary
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LLMInference & InterfacesUpdated 2026.04.28

Function Calling

Also known asTool Calling도구 호출Tool Use

In one line

Function calling is the interface that lets an LLM invoke predefined functions or APIs instead of just replying in natural language — the core mechanism behind AI agents.

Going deeper

Function calling is the interface that lets an LLM emit something like 'fetchOrder({orderId: 123})' instead of natural language. The host system runs the actual API call and feeds the result back to the model, which then completes the answer. It is what turns an LLM from a chatbot into a system that can act.

For marketers, this is the start of 'AI does, not just searches'. When a user says 'book me a room at XX hotel' and the AI calls your booking API directly, your presence in the AI's tool catalog becomes a new visibility variable.

Function calling is now generalising into protocols like MCP (Model Context Protocol). Zoom out and the whole space is really about how LLMs connect safely to the outside world.

Related terms

LLM

Structured Output

Structured output forces an LLM to reply in a predefined JSON or schema shape instead of free text — essential when you need to plug AI reliably into other systems.

LLM

LLM

A large language model (LLM) is a neural network trained on massive text corpora to understand and generate human language — the engine behind ChatGPT, Claude, Gemini and similar products.

LLM

RAG

RAG (Retrieval-Augmented Generation) lets an LLM fetch external documents at answer time and ground its response in them — the technique behind ChatGPT Search, Perplexity and most AI search products.

AI Agent

MCP

MCP (Model Context Protocol) is the open standard introduced by Anthropic for connecting LLMs to external tools and data sources in a consistent way.

AI Agent

Tool Use

Tool use is an LLM calling external APIs, calculators or search systems directly to ground its answers — the foundational behaviour of every agent.

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