What Is Tool Use in AI?

Tool use is an AI model's ability to call external tools, such as a search engine, a calculator, an API, or a database, to fetch information or take actions beyond generating text. Instead of answering only from what it knows, the model can reach out to a tool, use the result, and continue, which is what lets it act in the real world.

How tool use works

Tool use works by giving the model a set of tools it is allowed to call, each described by what it does and what inputs it needs. When answering would benefit from a tool, the model does not run it directly; it signals which tool to use and with what arguments. The surrounding application runs the tool, returns the result to the model, and the model carries on with that information in hand.

The mechanism that carries this out is usually function calling, where the model produces a structured request the software executes. Standards such as MCP aim to make connecting tools consistent across applications. Chaining several tool calls together, deciding what to do next based on each result, is the core of how AI agents operate.

Why tool use matters for AI

Tool use matters because it moves a model from talking about a task to actually doing it. A model on its own cannot look up today's data, run a calculation reliably, or change anything in another system; with tools, it can retrieve live information and take real actions. This is the foundation of agents and of any AI system that has to interact with the world rather than only produce text. At Custom AI Studio, connecting models to the right tools is how we build systems that act inside a client's software and data, rather than only answer questions.