An API development platform is software in which developers design, document and try out APIs, and save the tests that check them. It is also called an API workspace or an API client. Most developers have used one to send their first request to an API. An API is a fixed set of requests that one program accepts from other programs.
What does a developer actually do in it? She types the address of one API request, called an endpoint, for example https://api.example.in/claims/CLM-20481. She chooses the kind of request, such as GET to read data or POST to send data. She adds a key, a long secret code that proves she is allowed to call the API. Then she presses Send. The answer appears in the window. It shows a status code, such as 200 for success or 404 for "not found", the time taken, and the data itself. The data usually comes as JSON, a plain-text format of names and values, such as "status": "approved".
Take, for example, an IT services company in Pune that is building a claims API for a health insurer. Hospitals will call this API to check whether a patient's claim has been approved. The team first writes the API's description in the platform: each endpoint, the fields it accepts and the fields it returns. The description follows the OpenAPI specification, a standard file format for describing APIs. From it, the platform produces readable documentation for the hospitals' developers. It also creates a mock server, a fake version of the API that returns sample answers. So the insurer's app team can start building its screens two months before the real API is ready.
When the real API is ready, a developer sends a request for claim CLM-20481. The answer arrives in 180 milliseconds, with the status "approved" and the amount ₹42,500. She saves the request in a collection, a named folder of requests. To each request, she adds small tests, such as "the status code is 200" and "the answer arrives in under 500 milliseconds". After a month, the collection holds 60 requests and 150 tests.
These tests then run without anyone pressing Send. The CI/CD pipeline runs the whole collection on every code change, and stops the change if a test fails. This is a form of automated testing. Larger test suites, which try many more inputs, are the job of API testing tools. When the API goes live, it is published through the company's API gateway.
There is now a new kind of user: the AI agent, software that uses a language model to take actions on its own. An agent can call an API correctly only if it understands what each request does. So the platforms now help teams write descriptions that an agent can read, and test how an agent uses the API. The page on AI agent guardrails explains why the agent's access must also be limited.