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Allow LLMs to control a browser with Browserbase and Stagehand

Publisherbrowserbase
Repositorymcp-server-browserbase
LanguageTypeScript
Forks
358
Stars
3.3K
Available tools
0
Transport typestdio
Categories
LicenseApache-2.0
Links
  • Connect tools to AI workflows

    Browserbase exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    3.3K stars and 358 forks from the linked repository.

Browserbase MCP Server

cover

The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you're building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need.

This server provides cloud browser automation capabilities using Browserbase and Stagehand. It enables LLMs to interact with web pages, extract information, and perform automated actions.

This is a self-hostable version of the Browserbase hosted MCP server with the same tools and functionality. We recommend using the hosted version for the easiest setup.

Tools

This server exposes 6 tools that match the hosted Browserbase MCP server:

ToolDescriptionInput
startCreate or reuse a Browserbase session(none)
endClose the current Browserbase session(none)
navigateNavigate to a URL{ url: string }
actPerform an action on the page{ action: string }
observeObserve actionable elements on the page{ instruction: string }
extractExtract data from the page{ instruction?: string }

How to Setup

We currently support 2 transports for our MCP server, STDIO and SHTTP. We recommend you use SHTTP with our hosted MCP server to take advantage of the server at full capacity.

SHTTP (Hosted MCP):

Use the Browserbase hosted MCP server at https://mcp.browserbase.com/mcp. This is the easiest way to get started -- we host the server and provide the LLM costs for Gemini, the best performing model in Stagehand.

For full setup instructions, see the Browserbase MCP documentation.

If your client supports SHTTP:

json
{
  "mcpServers": {
    "browserbase": {
      "type": "http",
      "url": "https://mcp.browserbase.com/mcp"
    }
  }
}

If your client doesn't support SHTTP:

json
{
  "mcpServers": {
    "browserbase": {
      "command": "npx",
      "args": ["mcp-remote", "https://mcp.browserbase.com/mcp"]
    }
  }
}

STDIO (Self-Hosted):

You can either use our server hosted on NPM or run it completely locally by cloning this repo.

Note: If you want to use a different model you have to add --modelName to the args and provide that respective key as an arg. More info below.

To run via NPM (Recommended)

Go into your MCP Config JSON and add the Browserbase Server:

json
{
  "mcpServers": {
    "browserbase": {
      "command": "npx",
      "args": ["@browserbasehq/mcp"],
      "env": {
        "BROWSERBASE_API_KEY": "",
        "BROWSERBASE_PROJECT_ID": "",
        "GEMINI_API_KEY": ""
      }
    }
  }
}

That's it! Reload your MCP client and you're ready to go.

To run 100% local:

Option 1: Direct installation

bash
git clone https://github.com/browserbase/mcp-server-browserbase.git
cd mcp-server-browserbase
npm install && npm run build

Option 2: Docker

bash
git clone https://github.com/browserbase/mcp-server-browserbase.git
cd mcp-server-browserbase
docker build -t mcp-browserbase .

Then in your MCP Config JSON run the server:

Using Direct Installation

json
{
  "mcpServers": {
    "browserbase": {
      "command": "node",
      "args": ["/path/to/mcp-server-browserbase/cli.js"],
      "env": {
        "BROWSERBASE_API_KEY": "",
        "BROWSERBASE_PROJECT_ID": "",
        "GEMINI_API_KEY": ""
      }
    }
  }
}

Using Docker

json
{
  "mcpServers": {
    "browserbase": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "-e",
        "BROWSERBASE_API_KEY",
        "-e",
        "BROWSERBASE_PROJECT_ID",
        "-e",
        "GEMINI_API_KEY",
        "mcp-browserbase"
      ],
      "env": {
        "BROWSERBASE_API_KEY": "",
        "BROWSERBASE_PROJECT_ID": "",
        "GEMINI_API_KEY": ""
      }
    }
  }
}

Configuration

The Browserbase MCP server accepts the following command-line flags:

FlagDescription
--proxiesEnable Browserbase proxies for the session
--verifiedEnable Browserbase Verified Identity (Only for Scale Plan Users)
--advancedStealthDeprecated alias for --verified
--keepAliveEnable Browserbase Keep Alive Session
--contextId <contextId>Specify a Browserbase Context ID to use
--persistWhether to persist the Browserbase context (default: true)
--port <port>Port to listen on for HTTP/SHTTP transport
--host <host>Host to bind server to (default: localhost, use 0.0.0.0 for all interfaces)
--browserWidth <width>Browser viewport width (default: 1024)
--browserHeight <height>Browser viewport height (default: 768)
--modelName <model>The model to use for Stagehand (default: google/gemini-2.5-flash-lite)
--modelApiKey <key>API key for the custom model provider (required when using custom models)
--experimentalEnable experimental features (default: false)

These flags can be passed directly to the CLI or configured in your MCP configuration file.

Note: These flags can only be used with the self-hosted server (npx @browserbasehq/mcp or Docker).

Model Configuration

Stagehand defaults to using Google's Gemini 2.5 Flash Lite model, but you can configure it to use other models like GPT-4o, Claude, or other providers.

Important: When using any custom model (non-default), you must provide your own API key for that model provider using the --modelApiKey flag.

json
{
  "mcpServers": {
    "browserbase": {
      "command": "npx",
      "args": [
        "@browserbasehq/mcp",
        "--modelName",
        "anthropic/claude-sonnet-4.5",
        "--modelApiKey",
        "your-anthropic-api-key"
      ],
      "env": {
        "BROWSERBASE_API_KEY": "",
        "BROWSERBASE_PROJECT_ID": ""
      }
    }
  }
}

Note: The model must be supported in Stagehand. Check out the docs here.

Links

License

Licensed under the Apache 2.0 License.

Copyright 2025 Browserbase, Inc.

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "browserbase": {
      "command": "npx",
      "args": [
        "@browserbasehq/mcp"
      ],
      "env": {
        "BROWSERBASE_API_KEY": "",
        "BROWSERBASE_PROJECT_ID": ""
      }
    }
  }
}

Use Browserbase MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Browserbase is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add Browserbase as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the Browserbase MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "browserbase": {
      "command": "npx",
      "args": [
        "-y",
        "null"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the Browserbase MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the Browserbase MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use Browserbase to help me with this task?
Browserbase
Sure. I read it.
Here is what I found using Browserbase.

Frequently asked questions

What is the Browserbase MCP server used for?

Browserbase is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use Browserbase MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Browserbase with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use Browserbase MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With Browserbase connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect Browserbase MCP to TypingMind?

Browserbase runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does Browserbase MCP provide in TypingMind?

Browserbase exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use Browserbase MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If Browserbase requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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