Algorithm Engine for Web3 Builders

Welcome to the ❜embed Developer Hub.

Access decades of expertise in scalable, ML-powered personalization and moderation—productized into simple, modular APIs for app developers.

Integrate powerful AI models that predict the next on-chain or off-chain interactions.

To get started read on with the guides or use the TypeScript SDK right away.

TypeScript

import { getClient } from "@embed-ai/sdk"

// using the API_KEY_EMBED environment variable
const key = process.env.API_KEY_EMBED!;
// get the embed sdk client with your API Key
const client = getClient(key);

const feed = await client.feed.byUserId("16085", { top_k: 10 });

console.log(feed);

Learn how to use the SDK here with the ❜embed SDK Quickstart guide.

Studio SDK

For full control over the recommendation pipeline—search, features, scoring, and ranking—use the MBD Studio SDK:

import { StudioConfig, StudioV1 } from "mbd-studio-sdk"

const config = new StudioConfig({ apiKey: process.env.API_KEY });
const mbd = new StudioV1({ config });
mbd.forUser("polymarket-wallets", "0xYourWallet");

const candidates = await mbd.search()
  .index("polymarket-items")
  .includeVectors(true)
  .execute();
mbd.addCandidates(candidates);

const feed = mbd.getFeed();
console.log(feed);

Learn how to build a full pipeline with the Studio SDK Getting Started guide.