An API is like a menu for software: it lists what you can ask for and the format you will get back. AI companies offer APIs so developers can call their models from any app. API use is normally billed by usage and kept separate from consumer chat subscriptions.
How it works
Most web APIs follow a simple pattern. Your app sends an HTTP request to an address called an endpoint, for example one that generates text or speech. The request includes an API key, which identifies your account and authorises billing, plus parameters such as the model name, your prompt and settings like temperature. The server runs the job and returns a response, usually in JSON, a structured text format that code can read easily. Many AI APIs can stream results back piece by piece so text appears as it is generated. Providers enforce rate limits, capping how many requests or tokens you can use per minute, to protect their servers. Language model APIs usually charge per token, with output tokens often priced higher than input tokens; voice and image APIs charge per character, second or image. Documentation describes every endpoint, parameter and error code. Software development kits (SDKs) wrap the raw requests in a friendlier library for languages such as Python or JavaScript.
Why it matters
APIs are how AI gets inside the tools people already use. A business can add a model to its help desk, website or internal system instead of asking staff to copy text into a chatbot. Creators can automate captions, voiceovers or thumbnail drafts at scale. No-code platforms are largely friendly front ends over APIs. Understanding API keys, usage billing and rate limits helps you estimate costs, avoid surprise bills and keep your accounts secure.
Where you will see it
- Adding an AI assistant to a company website's help desk
- Generating voiceovers in bulk from a script spreadsheet
- Connecting a form to a CRM so new leads are saved automatically
- Pulling channel analytics into a custom dashboard
Limits and common misconceptions
- A leaked API key lets others run up charges on your account, so never paste it into public code.
- API pricing differs from chat subscriptions; heavy use can cost more than expected without spending limits.
- Providers can change or retire API versions, which may break apps that depend on them.
How it differs from related terms
- API vs MCP (Model Context Protocol) An API is any program-to-program interface; MCP is a specific open standard for connecting AI assistants to tools and data, often built on top of existing APIs.
- API vs Workflow automation Workflow automation tools connect apps for you, usually by calling their APIs behind a visual interface.
Tools that use it
Frequently asked questions
Is an API the same as a subscription to an AI chatbot?
No. A chat subscription gives a person access to an app. An API gives software access to the model, billed by usage such as tokens or characters. Many providers sell them separately, so paying for one does not usually include the other.
What is an API key?
An API key is a secret string that identifies your account when your software calls an API. It authorises requests and links usage to your billing. Treat it like a password: store it securely, never share it publicly and revoke it immediately if it leaks.
Do I need to know how to code to use an API?
Calling an API directly usually involves a little code, but no-code tools such as Zapier, Make and n8n let you use many APIs through visual steps. They handle the requests and responses so you can connect apps by filling in forms.
Related terms
- AI credits A usage unit that AI tools deduct from your plan each time you generate something, with costlier tasks using more credits.
- Algorithm A precise, finite sequence of steps that turns an input into an output, such as sorting a list or ranking search results.
- Artificial general intelligence (AGI) A hypothetical AI able to learn and perform nearly any intellectual task a human can, adapting to new problems without task-specific training.
- Artificial intelligence (AI) The field of building computer systems that perform tasks usually requiring human intelligence, such as understanding language, recognising images, predicting and generating content.
- Benchmark A standardised set of tasks with a fixed scoring method, used to measure and compare how well AI models perform a skill.