Getting started

Connect an AI assistant

Connect Dawnstack to Claude, ChatGPT or Cursor and your assistant can read the catalogue and these docs, then build against the API. No key to paste.

Dawnstack runs a Model Context Protocol server. Connect it to an assistant that speaks MCP and the assistant can read the model catalogue with live prices, read this documentation, check the balance, and run a request to verify a choice before writing it into your code.

The endpoint is:

https://api.dawnstackai.com/mcp

There is no key to paste. The first time your assistant calls it, you will be sent to a Dawnstack page to approve the connection, and that is all.

What the assistant can do

Tool	What it does
`list_models`	The catalogue: prices, context windows, measured speed, measured per-language cost
`get_model`	One model in detail, including which parameters it really supports
`search_docs`	Finds the pages here that answer a question
`get_docs`	Reads a page, or the whole reference
`get_account`	Balance, and which models it can currently call
`run_model`	One chat completion, billed to your balance, for checking a model behaves as expected

Everything except run_model is read-only and costs nothing. run_model spends your balance at the prices list_models reports, caps output at 512 tokens by default, and tells you what each call cost.

Connecting

Claude Code Cursor Claude ChatGPT

claude mcp add --transport http dawnstack https://api.dawnstackai.com/mcp

{
  "mcpServers": {
    "dawnstack": {
      "url": "https://api.dawnstackai.com/mcp"
    }
  }
}

Settings -> Connectors -> Add custom connector

Name: Dawnstack
URL:  https://api.dawnstackai.com/mcp

On a Team or Enterprise plan an owner adds it once in
Organization settings, and members then click Connect.

Settings -> Apps & Connectors -> Advanced -> Developer mode

Then add a connector with:
https://api.dawnstackai.com/mcp

Developer mode is available on paid plans, and a workspace
admin can turn it off for everyone.

Then ask for something. Build me a script that classifies support tickets, using Dawnstack, on a model that is cheap for Swahili. The assistant will read the catalogue, pick a model on the measured numbers rather than on a guess, and write code against this API.

What to expect the first time

Your assistant will ask you to connect. Approving takes you to a Dawnstack page that names the application by its hostname, says what it will be able to do, and waits for you to click. If you are not signed in, you sign in first and come straight back.

A new account has a starter balance, so the assistant can run real requests before you pay anything. When it runs out, run_model says so and tells you where to top up. Everything read-only keeps working.

What it is not

This is not a way to run production traffic. An assistant calling run_model in a loop is spending your balance on round trips, and the tool caps output low for that reason. Once you know which model you want, have the assistant generate code that calls chat completions with your own API key. That is the path everything else in these docs describes, and it is the one that streams, calls tools, returns structured output and accepts images.

Building without connecting

If you would rather not connect anything, hand your assistant llms-full.txt. It is this entire reference plus the live catalogue as one file, and it is the same text get_docs returns.