Tool Use (AI)

Tool use is what transforms an LLM from a text generator into an AI that can take actions in the real world. Without tools, an LLM can only produce text. With tools, it can: search the web, query databases, send emails, create calendar events, execute code, and interact with any system that has an API. The mechanism: (1) You define available tools as JSON schemas (function name, description, parameters). (2) The user sends a message. (3) The model decides whether to call a tool and generates the function call with arguments. (4) Your code executes the function and returns the result to the model. (5) The model uses the result to generate its final response. All major providers support this: OpenAI calls it "function calling," Anthropic calls it "tool use," Google calls it "function calling." The Model Context Protocol (MCP) is an emerging standard for sharing tool definitions across AI systems. Production considerations: validate all tool arguments (the model can generate invalid inputs), implement timeouts for external calls, handle tool failures gracefully, and log all tool invocations for debugging and auditing.