Quick Start
Get started with Orakle via the SDK, an MCP client, or the REST API.
You can use Orakle through the dashboard for ad-hoc pricing, or programmatically over the API. The SDK is the fastest path for application code, MCP drops pricing into any AI client, and the REST API is the raw surface for everything else.
1. Get an API key
Create a key in your dashboard. The dashboard is also where you see past runs, track usage, and manage billing. Keys are shown once — store it like a password.
2. SDK quick start
Install the TypeScript SDK:
pnpm add oraklenpm install orakleOne call submits the job, streams it, and resolves the final result. Use a
natural-language query, or pass request_type: "structured" with typed
product fields for the most accurate output (see the
TypeScript SDK for the structured shape):
import { OrakleClient } from "orakle";
const orakle = new OrakleClient({ apiKey: process.env.ORAKLE_API_KEY! });
const result = await orakle.priceCheck({
request_type: "nl",
query: "iPhone 15 Pro 128GB Grade B unlocked",
geography: "US",
});
console.log(result.fused_distribution.quantiles);
// { "0.1": 780, "0.5": 870, "0.9": 960 }See TypeScript for the TypeScript client.
3. MCP quick start
Connect any MCP-capable AI app and let the model price products in chat. The server URL is:
https://api.orakle.xyz/v1/mcpIn an AI web app, add it as a custom connector under Settings →
Connectors. On first use your browser opens to authorize. Then ask the
model to price something — it calls the get_pricing tool directly. Full
setup in MCP.
What you get
Every completed pricing job returns:
product_profile— the normalized product Orakle priced.fused_distribution— the calibrated price distribution:quantiles(e.g."0.1","0.5","0.9") and the marketcurrency. Use the median for a point estimate, the spread for confidence.scenario_forecast— a scenario-weighted forward view (may benull).
The spread is the signal
A wide distribution means the market is genuinely uncertain about this item — that is information, not noise. Don't collapse it to a single number too early.
Next
TypeScript SDK
Typed client that wraps submit, stream, and result into one call.
MCP Server
Connect any MCP-capable AI app and price products in chat.
REST API
The raw surface — submit a job, stream progress over SSE, read the result.
Built for LLMs too
Every page is available as raw Markdown — append .md to any docs URL, or use
/llms.txt and /llms-full.txt to feed the
entire documentation set to an agent.