How to Set Up the Monetzly SDK in Vercel AI SDK (Next.js)

Overview

Before you can monetize a Vercel AI SDK (Next.js) app, the Monetzly client needs configuring and connecting. This is a one-time setup: an API key, the ad-server address, and SSL settings, then a connection you open when a request starts and close when it ends.

Keep the API key in an environment variable, never in source. Use a non-SSL localhost address in development and your real ad-server host in production.

Vercel AI SDK (Next.js) apps are usually built for streaming chat UIs, Next.js AI apps, and edge/serverless LLM routes, so set up the Monetzly SDK typically comes up while a user is mid-conversation, the moment where monetization has to be additive rather than disruptive.

How this works on Vercel AI SDK (Next.js)

Vercel's streamText() exposes a textStream of plain strings. Wrap it in an async generator that yields { content: text } and pass that into sdk.inject(); then stream the injected tokens back in your Route Handler Response. Both APIs are documented, so this is a direct fit.

Because Monetzly's inject() accepts any async token stream, the Vercel AI SDK (Next.js) side of this task is just mapping your output to it, no rewrite of your Vercel AI SDK (Next.js) model call.

Steps

1. Install the SDK (or, for a Python Vercel AI SDK (Next.js) stack, generate gRPC stubs from the shipped tps_alter.proto).
2. Create a config with your API key, server address, and SSL flag.
3. Open a connection at the start of a request and close it when the response finishes.

Integration snippet

import { streamText } from "ai";
import { google } from "@ai-sdk/google";
import { MonetzlySDK } from "@monetzly/server-sdk";

const sdk = new MonetzlySDK({
  apiKey: process.env.MONETZLY_API_KEY!,
  serverAddress: process.env.MONETZLY_SERVER_ADDRESS!,
});

export async function POST(req: Request) {
  const { prompt } = await req.json();
  await sdk.connect();
  const { textStream } = streamText({ model: google("gemini-2.0-flash"), prompt });

  // Adapt Vercel's string stream to Monetzly's TokenChunk shape.
  async function* asChunks() {
    for await (const text of textStream) yield { content: text };
  }

  const enc = new TextEncoder();
  const body = new ReadableStream({
    async start(c) {
      for await (const t of sdk.inject(asChunks(), { prompt }))
        c.enqueue(enc.encode(t.content ?? ""));
      await sdk.disconnect();
      c.close();
    },
  });
  return new Response(body, { headers: { "Content-Type": "text/plain; charset=utf-8" } });
}

Frequently asked questions

Related