API

What is an API?

An API, or application programming interface, is a defined way for software systems to exchange requests, data, or actions. It specifies how one program can ask another program to perform an operation without needing to know its internal implementation.

AI agents often access external systems through APIs, including search, calendars, databases, payment services, ticketing tools, and business applications.

How an API works

An API usually defines available operations, required inputs, authentication rules, and response formats. A client sends a request to an operation or endpoint. The service processes it and returns a response containing data, a status, or an error.

For example, a calendar API may accept a request containing a start time, duration, and participant list. It can return a newly created event or an error explaining why creation failed.

Different APIs use different communication styles and protocols. For an agent, the important point is that application code translates an intended action into the API’s required request and interprets the response.

API versus tool

An API exposes a software interface. An agent tool is a capability presented to the model. A tool may wrap one API endpoint, combine several API calls, query a local database, or perform an operation without using a network API.

This wrapper can simplify a complex service and expose only safe, task-relevant operations. The model sees the tool definition and schema, while credentials and provider-specific details remain in application code.

API versus function calling

Function calling is the model’s structured request for application code to run a predefined function. That function may call an API. The two are connected but not interchangeable: function calling is part of model integration, while an API is a software-to-software interface.

Reliability and safety

API calls can fail because of invalid input, expired credentials, unavailable services, rate limits, permission problems, or changed data. A successful network response may still represent only partial completion.

Agent systems should validate inputs, protect credentials, apply timeouts, interpret errors clearly, and avoid blindly retrying write operations. High-impact API actions should use narrow scopes, confirmations, and audit records.

Why APIs matter for agents

APIs let agents obtain current information and take actions beyond generated text. They connect model decisions to real systems, which is where much of an agent’s practical value—and risk—comes from.

The model should not receive unrestricted access merely because an API exists. Builders should expose purpose-built tools, enforce authorization outside the model, and return clear results for the next decision. See [Tool Use in AI Agents](/tool-use-in-ai-agents/) for the full integration pattern.