Browserbasehq Mcp Browserbase

ai.smithery由 smithery.ai 发布官方发布者v2.2.0更新于 Oct 24, 2026

Provides cloud browser automation capabilities using Stagehand and Browserbase, enabling LLMs to i…

发布方自己的服务：222wcnm Bilistalkermcp

已验证Streamable HTTP可网页运行网页搜索与抓取浏览器自动化

概览

AI 生成的概览

基于 Browserbase 与 Stagehand 的云端浏览器自动化服务器，让助手开启会话、导航页面、执行操作、观察元素并提取数据。

可以做什么
  • 创建或复用 Browserbase 云端浏览器会话，并在结束时关闭
  • 将浏览器导航到指定网址
  • 在页面上执行操作，并观察可交互元素
  • 按指令从当前页面提取数据
适用场景
适合需要助手操控真实云端浏览器的场景，例如填写表单、点击浏览网站，或从普通 HTTP 抓取无法处理的页面中提取结构化信息。README 说明该仓库已归档，建议改用 Browserbase 托管版本。
运行要求
远程端点位于 server.smithery.ai，需在 Authorization 请求头中提供 bearer 令牌。自托管版本需要 Node.js（npx @browserbasehq/mcp）或 Docker，并配置 BROWSERBASE_API_KEY、BROWSERBASE_PROJECT_ID，默认 Stagehand 模型还需 GEMINI_API_KEY；使用自定义模型需提供 --modelApiKey。
安装前请注意
README 明确说明仓库已归档、不再维护，建议优先使用托管版本。自托管需要 Browserbase API 密钥与项目 ID，非默认模型还需模型服务商密钥。助手可对真实网页执行操作，可能提交表单或改变远端状态，页面内容会交由 Browserbase 及所选模型服务商处理。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Browserbasehq Mcp Browserbase，将其添加到工作区。
  2. 连接 Authorization token 凭据。它们会被私密存储，绝不会在公开页面上展示。
  3. 为需要使用其工具的对话启用该服务。

Web executable，通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体，或 SourceWeft 对话中。智能体会读取该服务器的安装指南，先向你展示发布者、端点和登录方式，经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/ai.smithery%2Fbrowserbasehq-mcp-browserbase/install.md，并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前，先告诉我它的发布者、端点和登录方式，等我确认。不要把 API 密钥写进命令或我会提交的文件；问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

{
  "mcpServers": {
    "browserbasehq-browserbase": {
      "type": "http",
      "url": "https://server.smithery.ai/@browserbasehq/mcp-browserbase/mcp",
      "headers": {
        "Authorization": "Bearer <YOUR_TOKEN>"
      }
    }
  }
}

README

Browserbase MCP Server

Archived

This repository is archived and no longer maintained.

It was originally published as a reference implementation and is retained for historical purposes. It should not be interpreted as representative of Browserbase's current production services or implementation.

[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.gitcd mcp-server-browserbasenpm install && npm run build
Option 2: Docker
bash
git clone https://github.com/browserbase/mcp-server-browserbase.gitcd mcp-server-browserbasedocker 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.

来源：README.md，提交 3e6f534

工具

0
SourceWeft 尚未读取此服务器的工具。

版本历史

1
  1. v2.2.0最新Sep 16, 2026

评分

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