I built a pricing API for LLMs — then realized the real users might not be human

Klikk her: LLM Price Watch started as a simple problem: comparing per-token pricing across Claude, GPT, Gemini, DeepSeek, and Grok meant opening five pricing pages and doing the math by hand every time a new model dropped. So I built a calculator. Then I built an API behind it. Then I noticed something about who was actually going to call that API. The obvious version The first version of the API was exactly what you'd expect: GET /v1/models — every tracked model with current pricing GET /v1/models/:id — a single model GET /v1/calculate?model=X&input_tokens=N&output_tokens=N — cost for a specific call Straightforward. A human developer hits /calculate , gets a number, builds their cost estimate into a dashboard somewhere. Done. The part that changed the design The actual differentiator turned out to be a fourth endpoint: GET /v1/recommend?use_case=X . Instead of just returning prices, it returns a recommendation — which model fits a given use case (long-document summarization, high-volume classification, coding assistance, customer support) based on both price and the editorial analysis already written for the comparison pages on the site. Once that endpoint existed, the actual audience for this API stopped being "a developer building a cost dashboard" and started including something else: AI agents doing their own tool selection at runtime. An agent framework deciding which model to route a task to doesn't want to read a blog post — it wants a structured answer to "given this use case, what should I use, and what will it cost me." That's a tool call, not a page view. That reframing changed a few concrete decisions: CORS is wide open on purpose. This isn't an API with a dashboard in front of it — it's meant to be called directly from wherever the calling code lives, including client-side agent code. No API key required (for now). Every bit of friction between "an agent wants this data" and "an agent gets this data" is friction against the actual use case. A paid tie