Agent

What is `agent()?`

agent.execute("apply for a job at browserbase")

agent turns high level tasks into fully autonomous browser workflows. You can customize the agent by specifying the LLM provider and model, setting custom instructions for behavior, and configuring max steps.

Why use `agent()`?

Multi-Step Workflows

Execute complex sequences automatically.

Visual Understanding

Sees and understands web interfaces like humans do using computer vision.

Using `agent()`

There are two ways to create agents in Stagehand:

Computer Use Agents

Use computer use agents with specialized models from OpenAI or Anthropic:

const agent = stagehand.agent({
  provider: "anthropic",
  model: "claude-sonnet-4-20250514",
  instructions: "You are a helpful assistant that can use a web browser.",
  options: {
    apiKey: process.env.ANTHROPIC_API_KEY,
  },
});
await agent.execute("apply for a job at Browserbase")

agent = stagehand.agent(
    model="claude-sonnet-4-20250514",
    instructions="You are a helpful assistant that can use a web browser.",
    options={
        "api_key": os.getenv("ANTHROPIC_API_KEY"),
    },
)
await agent.execute("apply for a job at Browserbase")

View or run the example template here

Use Stagehand Agent with Any LLM

Use the agent without specifying a provider to utilize any model or LLM provider:

Non CUA agents are currently only supported in TypeScript

TypeScript

const agent = stagehand.agent();
await agent.execute("apply for a job at Browserbase")

MCP Integrations

Agents can be enhanced with external tools and services through MCP (Model Context Protocol) integrations. This allows your agent to access external APIs and data sources beyond just browser interactions.

const agent = stagehand.agent({
  provider: "openai",
  model: "computer-use-preview",
  integrations: [
    `https://mcp.exa.ai/mcp?exaApiKey=${process.env.EXA_API_KEY}`,
  ],
  instructions: `You have access to web search through Exa. Use it to find current information before browsing.`,
  options: {
    apiKey: process.env.OPENAI_API_KEY,
  },
});

await agent.execute("Search for the best headphones of 2025 and go through checkout for the top recommendation");

import { connectToMCPServer } from "@browserbasehq/stagehand";

const supabaseClient = await connectToMCPServer(
  `https://server.smithery.ai/@supabase-community/supabase-mcp/mcp?api_key=${process.env.SMITHERY_API_KEY}`
);

const agent = stagehand.agent({
  provider: "openai",
  model: "computer-use-preview",
  integrations: [supabaseClient],
  instructions: `You can interact with Supabase databases. Use these tools to store and retrieve data.`,
  options: {
    apiKey: process.env.OPENAI_API_KEY,
  },
});

await agent.execute("Search for restaurants and save the first result to the database");

MCP integrations enable agents to be more powerful by combining browser automation with external APIs, databases, and services. The agent can intelligently decide when to use browser actions versus external tools.

Stagehand uses a 1288x711 viewport by default (the optimal size for Computer Use Agents). Other viewport sizes may reduce performance. If you need to modify the viewport, you can edit in the Browser Configuration.

Available Models

Use specialized computer use models (e.g., computer-use-preview from OpenAI or claude-sonnet-4-20250514 from Anthropic)

Available Models

Check out the guide on how to use different models with Stagehand.

Agent Execution Configuration

Control the maximum number of steps the agent can take to complete the task using the maxSteps parameter.

// Set maxSteps to control how many actions the agent can take
await agent.execute({
  instruction: "Sign me up for a library card",
  maxSteps: 15 // Agent will stop after 15 steps if task isn't complete
});

# Set max_steps to control how many actions the agent can take
result = await agent.execute({
    "instruction": "Sign me up for a library card",
    "max_steps": 15  # Agent will stop after 15 steps if task isn't complete
})

For complex tasks, increase the maxSteps limit and check task success.

// Complex multi-step task requiring more actions
const result = await agent.execute({
  instruction: "Find and apply for software engineering jobs, filtering by remote work and saving 3 applications",
  maxSteps: 30, // Higher limit for complex workflows
});

// Check if the task completed successfully
if (result.success === true) {
  console.log("Task completed successfully!");
} else {
  console.log("Task failed or was incomplete");
}

# Complex multi-step task requiring more actions
result = await agent.execute({
    "instruction": "Find and apply for software engineering jobs, filtering by remote work and saving 3 applications",
    "max_steps": 30  # Higher limit for complex workflows
})

# Check if the task completed successfully
if result.success == True:
    print("Task completed successfully!")
else:
    print("Task failed or was incomplete")

Best Practices

Following these best practices will improve your agent’s success rate, reduce execution time, and minimize unexpected errors during task completion.

Start on the Right Page

Navigate to your target page before executing tasks:

Do this
Don't do this

await page.goto('https://github.com/browserbase/stagehand');
await agent.execute('Get me the latest PR on the stagehand repo');

await page.goto("https://github.com/browserbase/stagehand")
result = await agent.execute("Get me the latest PR on the stagehand repo")

await agent.execute('Go to GitHub and find the latest PR on browserbase/stagehand');

result = await agent.execute("Go to GitHub and find the latest PR on browserbase/stagehand")

Be Specific

Provide detailed instructions for better results:

Do this
Don't do this

await agent.execute("Find Italian restaurants in Brooklyn that are open after 10pm and have outdoor seating");

result = await agent.execute("Find Italian restaurants in Brooklyn that are open after 10pm and have outdoor seating")

await agent.execute("Find a restaurant");

result = await agent.execute("Find a restaurant")

Troubleshooting

Agent is stopping before completing the task

Problem: Agent stops before finishing the requested taskSolutions:

Check if the agent is hitting the maxSteps limit (default is 20)
Increase maxSteps for complex tasks: maxSteps: 30 or higher
Break very complex tasks into smaller sequential executions

// Increase maxSteps for complex tasks
await agent.execute({
  instruction: "Complete the multi-page registration form with all required information",
  maxSteps: 40 // Increased limit for complex task
});

// Or break into smaller tasks with success checking
const firstResult = await agent.execute({
  instruction: "Fill out page 1 of the registration form", 
  maxSteps: 15
});

// Only proceed if the first task was successful
if (firstResult.success === true) {
  await agent.execute({
    instruction: "Navigate to page 2 and complete remaining fields",
    maxSteps: 15
  });
} else {
  console.log("First task failed, stopping execution");
}

Agent is failing to click the proper elements

Problem: Agent clicks on wrong elements or fails to interact with the correct UI componentsSolutions:

Ensure proper viewport size: Stagehand uses 1288x711 by default (optimal for Computer Use models)
Avoid changing viewport dimensions as other sizes may reduce performance

First Steps

The Basics

Configuration

Best Practices

Integrations

Reference

What is `agent()?`

Why use `agent()`?

Multi-Step Workflows

Visual Understanding

Using `agent()`

Computer Use Agents

Use Stagehand Agent with Any LLM

MCP Integrations

Available Models

Available Models

Agent Execution Configuration

Best Practices

Start on the Right Page

Be Specific

Troubleshooting

Next steps

Act

Extract

​What is agent()?

​Why use agent()?

Multi-Step Workflows

Visual Understanding

​Using agent()

​Computer Use Agents

​Use Stagehand Agent with Any LLM

​MCP Integrations

​Available Models

Available Models

​Agent Execution Configuration

​Best Practices

​Start on the Right Page

​Be Specific

​Troubleshooting

​Next steps

Act

Extract

What is `agent()?`

Why use `agent()`?

Using `agent()`

Computer Use Agents

Use Stagehand Agent with Any LLM

MCP Integrations

Available Models

Agent Execution Configuration

Best Practices

Start on the Right Page

Be Specific

Troubleshooting

Next steps