# Browserbase MCP Server (`agentify/browserbase-mcp-server`) Actor

A Model Context Protocol (MCP) server that provides browser automation capabilities using Browserbase.

- **URL**: https://apify.com/agentify/browserbase-mcp-server.md
- **Developed by:** [agentify](https://apify.com/agentify) (community)
- **Categories:** AI, MCP servers, Open source
- **Stats:** 99 total users, 1 monthly users, 100.0% runs succeeded, 6 bookmarks
- **User rating**: 5.00 out of 5 stars

## Pricing

Pay per event + usage

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## 🅱️ Browserbase MCP Server

[![Browserbase MCP Server](https://apify.com/actor-badge?actor=mcp-servers/browserbase-mcp-server)](https://apify.com/mcp-servers/browserbase-mcp-server)

This Actor is a wrapper for the [browserbase](https://github.com/browserbase/mcp-server-browserbase) MCP server.

This server provides cloud browser automation capabilities using [Browserbase](https://www.browserbase.com/). This server enables LLMs to interact with web pages, and take screenshots, in a cloud browser environment.

### Connection URL

MCP clients can connect to this server at:

```text
https://mcp-servers--browserbase-mcp-server.apify.actor/mcp
```

### Client Configuration

To connect to this MCP server, use the following configuration in your MCP client:

```json
{
  "mcpServers": {
    "browserbase": {
      "url": "https://mcp-servers--browserbase-mcp-server.apify.actor/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_APIFY_TOKEN"
      }
    }
  }
}
```

**Note:** Replace `YOUR_APIFY_TOKEN` with your actual Apify API token. You can find your token in the [Apify Console](https://console.apify.com/account/integrations).

### 🚩 Claim this MCP server

All credits to the original authors of https://github.com/browserbase/mcp-server-browserbase

To claim this server, please write to <ai@apify.com>

### 🚀 Features

| Feature            | Description                               |
| ------------------ | ----------------------------------------- |
| Browser Automation | Control and orchestrate cloud browsers    |
| Data Extraction    | Extract structured data from any webpage  |
| Console Monitoring | Track and analyze browser console logs    |
| Screenshots        | Capture full-page and element screenshots |
| JavaScript         | Execute custom JS in the browser context  |
| Web Interaction    | Navigate, click, and fill forms with ease |

### 🔍 Use cases

- 🌐 Web navigation and form filling
- 📋 Structured data extraction
- 🧪 LLM-driven automated testing
- 🤖 Browser automation for AI agents

### 🧰 Tools

| Tool Name                          | Description                                                                 |
| ---------------------------------- | --------------------------------------------------------------------------- |
| multi\_browserbase\_stagehand\_session\_create | Creates multiple browser sessions for parallel tasks like data scraping or A/B testing. Each session is isolated with its own cookies and state. |
| multi\_browserbase\_stagehand\_session\_list | Lists all active browser sessions with their IDs, names, and details for easy management. |
| multi\_browserbase\_stagehand\_session\_close | Closes a specific browser session to free up resources and avoid extra charges. |
| multi\_browserbase\_stagehand\_navigate\_session | Navigates to a URL in a specific browser session. |
| multi\_browserbase\_stagehand\_act\_session | Performs simple actions on page elements, like clicking buttons or typing text, in a specific session. |
| multi\_browserbase\_stagehand\_extract\_session | Pulls structured data or text from a web page based on your instructions, for a specific session. |
| multi\_browserbase\_stagehand\_observe\_session | Finds interactive elements on a page, like buttons or forms, to help with actions, for a specific session. |
| multi\_browserbase\_stagehand\_get\_url\_session | Retrieves the current URL of a specific browser session. |
| browserbase\_stagehand\_get\_all\_urls | Gets the current URLs for all active browser sessions. |
| browserbase\_session\_create         | Sets up a single browser session for basic web automation tasks. |
| browserbase\_session\_close          | Closes the current browser session and cleans up resources. |
| browserbase\_stagehand\_navigate     | Navigates to a URL in the browser. |
| browserbase\_stagehand\_act          | Performs simple actions on page elements, like clicking buttons or typing text. |
| browserbase\_stagehand\_extract      | Pulls structured data or text from a web page based on your instructions. |
| browserbase\_stagehand\_observe      | Finds interactive elements on a page, like buttons or forms, to help with actions. |
| browserbase\_screenshot             | Captures a screenshot of the current page for reference. |
| browserbase\_stagehand\_get\_url      | Retrieves the current URL of the browser page. |

### 💸 Pricing

| Event                              | Description                                                   | Price (USD) |
| ---------------------------------- | ------------------------------------------------------------- | ----------- |
| Actor start                        | Flat fee for starting an Actor run.                           | $0.10       |
| Actor runtime per minute           | Flat fee for each minute of Actor runtime.                   | $0.003       |
| Browserbase tool call              | Fixed fee for each browser automation tool call. | $0.036      |

# Actor input Schema

## Actor input object example

```json
{}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("agentify/browserbase-mcp-server").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("agentify/browserbase-mcp-server").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call agentify/browserbase-mcp-server --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,agentify/browserbase-mcp-server"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/3tgBSCvGEXMjuHQDM/builds/TguYcWPyEDkzzhc0R/openapi.json