Good AI API documentation should help developers answer three questions quickly: which model should I use, which endpoint does it support, and how do I connect it to my application?

ModAPI documentation is organized around practical integration work: model discovery, endpoint formats, API keys, usage tracking, and multimodal model access.

What to check first

Before integrating a model, developers should confirm:

  • The model name used by the API.
  • The supported endpoint format.
  • Input and output modalities.
  • Context and output limits.
  • Streaming support where relevant.
  • Usage and cost behavior.
  • Any model-specific request parameters.

Endpoint formats

AI providers do not all expose the same API shape. Some workflows are OpenAI-compatible, some follow Claude-style messages, some use Gemini-style endpoints, and some multimodal APIs use task submission and polling.

ModAPI documentation should be used to confirm the right endpoint style for each model and workflow.

Practical workflow

Start from the model catalog, choose a model, review its supported endpoint, generate or use an API key, then test a small request before adding the model to production traffic.