Agent tools: What they are, how they work, and how AI agents use them

Agent tools are essential functions and services that enable AI agents to interact with external systems and perform tasks beyond mere text generation. These tools transform an AI model from just generating language to executing actions such as querying databases, sending emails, and running workflows. The utility of AI agents largely depends on the diversity and specificity of the tools they use, which are categorized into web search, retrieval, computation, file manipulation, computer-use, and business productivity tools. The distinction between agent tools and skills is crucial; tools perform discrete actions while skills guide the reasoning process for problem-solving. The Model Context Protocol (MCP) standardizes tool integration, allowing AI agents to dynamically discover and use tools across different services without custom integration. This standardization, coupled with the ReAct pattern—a cycle of reasoning and action—enhances the reliability and functionality of AI agents. Effective tool selection and execution are paramount, necessitating precise tool definitions and robust guardrails to ensure safe and accurate agent operations. Retrieval tools are particularly significant as they provide the contextual data necessary for informed decision-making, highlighting the importance of connected knowledge systems like knowledge graphs for enhanced agent performance.