Vercel AI SDK

In this guide, you’ll build an agent that researches the latest TypeScript release and reports what it found, its sources, and the tool cost.

Add to an existing agent

Use your existing model and prompt with AgentMuxer tools:

import { agentmuxer } from "@agentmuxer/sdk/ai-sdk";
import { ToolLoopAgent } from "ai";

const mux = await agentmuxer();
try {
  const agent = new ToolLoopAgent({ model, tools: mux.tools });
  const result = await agent.generate({ prompt });
  console.log(result.text);
} finally {
  await mux.close();
}

The helper returns { tools, close }. It does not choose a model or run the agent.

Before you start

Node.js 22.18 or later with ESM; see compatibility.
An AgentMuxer application key and credits for paid calls.
An OpenAI API key for the model.

This example asks the agent to spend up to $0.10 on one tool call. Model charges are separate. Set an application spending limit if you need a hard cap; the prompt alone doesn’t enforce one.This example cannot collect payment confirmation. Configure your account for unattended purchases before running it. This setting also affects your personal agents.

Install

In a new directory, create an ESM project and install the integration:

mkdir my-agent
cd my-agent
npm init -y
npm pkg set type=module
npm install @agentmuxer/sdk @ai-sdk/mcp ai @ai-sdk/openai zod

Set your keys

Set both keys in your terminal:

export AGENTMUXER_API_KEY='your-application-key'
export OPENAI_API_KEY='your-model-provider-key'

No browser sign-in is needed. Keep both keys on your server and out of source control.

Create your agent

Save this as agent.ts:

agent.ts

import { agentmuxer } from "@agentmuxer/sdk/ai-sdk";
import { openai } from "@ai-sdk/openai";
import { ToolLoopAgent } from "ai";

const prompt = `Use AgentMuxer to research the latest TypeScript release.
Summarize three changes with sources and report the tool cost.
Spend at most $0.10 on one tool call. Stop if it costs more.`;

const mux = await agentmuxer();
try {
  const agent = new ToolLoopAgent({
    model: openai("gpt-5.5"),
    tools: mux.tools,
  });
  const result = await agent.generate({ prompt });
  console.log(result.text);
} finally {
  await mux.close();
}

Run

node agent.ts

The example asks the agent to print:

Three TypeScript release changes.
Sources for the summary.
The actual tool cost, or the reason it could not complete the purchase.

To try another task, edit prompt. Include the spending you allow.

Stream the result

In agent.ts, replace the agent.generate() call and console.log(result.text) with:

const result = await agent.stream({ prompt });
for await (const part of result.textStream) {
  process.stdout.write(part);
}

Keep this inside the try block. The existing finally closes the connection after you consume the stream. For an HTTP response stream, attach cleanup to completion, error, and cancellation; do not close the connection when you merely return the stream.

Connection options and approvals

The helper accepts initializationOptions and onUncaughtError and disables automatic MCP tool-call retries. Configure model behavior and tool permissions in your AI SDK agent. See the SDK reference. In SDK 0.1.0, the helper does not expose a flow for resuming AgentMuxer purchase-confirmation requests. Use unattended purchases as described above or a client with confirmation support. Application spending limits still apply.

Applications and keys

Manage credentials and spending limits.

Run in production

Handle deployment, failures, and tracing.

Get started

Integrations

Your application

Before you start

Stream the result

Connection options and approvals

Applications and keys

Run in production

​Before you start

​Stream the result

​Connection options and approvals

Applications and keys

Run in production

Before you start

Stream the result

Connection options and approvals