How-to guide
How to Inject Ads Into a Streaming Response in n8n
This guide shows how to inject ads into a streaming response in a n8n app, the goal being to wrap the LLM token stream so contextual ads appear inside the assistant's reply. It builds on the Monetzly server SDK, so the approach is specific to how n8n produces and streams responses.
Overview
This is the core of monetizing a n8n app: instead of returning the raw model stream, you pass it through Monetzly, which injects contextual, labelled ads into the token stream and hands you back the enhanced stream to forward to the client.
You keep your existing n8n model call untouched. Injection is additive — a wrapper around the stream you already produce, keyed on the session and the live prompt so the ad matches what the user is asking about.
n8n apps are usually built for automated AI workflows, chatbot backends, and agent orchestration, so inject ads into a streaming response typically comes up while a user is mid-conversation, the moment where monetization has to be additive rather than disruptive.
How this works on n8n
n8n runs on Node, so a Code node (or a small custom node) can import @monetzly/server-sdk and wrap the token output of an upstream LLM node. Because n8n items are usually discrete rather than a live token stream, confirm whether you inject over a buffered response or a true stream for your workflow.
Because Monetzly's inject() accepts any async token stream, the n8n side of this task is just mapping your output to it, no rewrite of your n8n model call.
Steps
- Produce your n8n response as a token stream as you already do.
- Pass that stream into the Monetzly injection call with the session id and prompt.
- Forward the enhanced tokens to the client (SSE, WebSocket, or your existing transport).
Integration snippet
// n8n Code node (runOnceForEachItem). TODO_VERIFY: streaming vs buffered output.
import { MonetzlySDK } from "@monetzly/server-sdk";
const sdk = new MonetzlySDK({
apiKey: $env.MONETZLY_API_KEY,
serverAddress: $env.MONETZLY_SERVER_ADDRESS,
});
await sdk.connect();
const llmText = $json.text; // output from the previous LLM node
async function* asChunks() { yield { content: llmText }; }
let out = "";
for await (const t of sdk.inject(asChunks(), { prompt: $json.prompt })) out += t.content ?? "";
await sdk.disconnect();
return { json: { text: out } };Frequently asked questions
Start monetizing in about 5 minutes
Wrap your existing LLM response stream with the Monetzly SDK and earn on every session, no paywall required.