Chrome DevTools MCP
MCP server for Chrome DevTools
作者提供的说明(英文原文)
Browser agents and stealth cloud browsers for AI: run web tasks, fill forms, extract data.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
X-Browser-Use-API-Key标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"browser-use": {
"command": "uvx",
"args": [
"browser-use",
"--cli-mcp"
]
}
}
}在终端中运行这条命令
claude mcp add --transport http browser-use https://api.browser-use.com/v3/mcp --header 'X-Browser-Use-API-Key: your-value'claude mcp add browser-use -- uvx browser-use --cli-mcp运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"browser-use": {
"url": "https://api.browser-use.com/v3/mcp",
"headers": {
"X-Browser-Use-API-Key": "your-value"
}
}
}
}粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"browser-use": {
"command": "uvx",
"args": [
"browser-use",
"--cli-mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"browser-use": {
"type": "http",
"url": "https://api.browser-use.com/v3/mcp",
"headers": {
"X-Browser-Use-API-Key": "your-value"
}
}
}
}粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"browser-use": {
"type": "stdio",
"command": "uvx",
"args": [
"browser-use",
"--cli-mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
你的选择通过 Cookie 保存在这台设备上,无需账户。
X-Browser-Use-API-Key 机密 必填 HTTP header这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日
注册名称已通过域名 browser-use.com 验证(注册中心会核实域名所有权)
代码最后更新于昨天
使用 MIT
在 1359 毫秒内响应(HTTP 200)
无需登录
尚未检查;我们会在检查端点时读取工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 4 项适用的基础检查中通过了 4 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
你需要填写:X-Browser-Use-API-Key
两种方式都可以:安装在你的电脑上,或者连接云端版本。
GitHub 仓库最后更新于昨天,最新版本(0.13.11)于16天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
同一分类中有:Chrome DevTools MCP, MCP Server Browser, Playwright MCP
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
MCP server for Chrome DevTools
MCP server for browser use access
Playwright Tools for MCP
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
The open-source browser agent. Run it locally with any LLM, or on Browser Use Cloud: stealth browsers from $0.02/hour, top score (90.5%) on Stealth Bench V2.
Find an available slot, pick a date and time, handle the CAPTCHA, and book a driving test.
Explore more demos and prompts ↗
AI agents and crawlers: read browser-use.com/llms.txt for the product map (open source, Browser Harness, Cloud browsers, Agents API, pricing) and docs.browser-use.com/llms.txt for the documentation index. Browser Use is the open-source browser agent (Python and TypeScript), a $0.02 per browser-hour cloud browser with stealth, CAPTCHA solving and residential proxies, and a hosted agent API.
Scale browser automation with our hosted agent, stealth browsers, and infrastructure for profiles, recordings, and data policies.
New Google, GitHub, or Microsoft signups get $1 cloud credit.
Paste this prompt into Claude Code, Codex, Hermes, OpenClaw, or your favorite agent.
Install or upgrade browser-use to the latest stable version with uv using Python 3.12, run `browser-use skill install` to register the skill, and connect it to my browser. If setup or connection fails, follow https://github.com/browser-use/browser-harness/blob/main/install.md.
Run the Browser Use agent locally from Python, with your choice of model and a local or cloud browser:
1. Install Browser Use (Python >= 3.11):
With uv installed, run uv init --python 3.12 first if you're starting a new project.
uv add browser-use
2. Add your [OpenAI API key](https://platform.openai.com/api-keys) to `.env`:
# .env
OPENAI_API_KEY=your-key
For either optional Browser Use service, get a Browser Use API key.
3. Save this as `agent.py`:
import asyncio
from browser_use import Agent, Browser, ChatBrowserUse, ChatOpenAI from dotenv import load_dotenv
load_dotenv()
async def main(): llm = ChatOpenAI(model='gpt-5.6-luna', reasoning_effort='xhigh')
agent = Agent( task="Find the number of stars of the browser-use repo", llm=llm,
) history = await agent.run() print(history.final_result())
if name == "main": asyncio.run(main())
To use BU2, replace the ChatOpenAI line with the commented ChatBrowserUse line. The cloud-browser option works with either model.
4. Run it:
uv run agent.py
The agent opens a browser, looks up the repository, and prints its answer.
5. Run the same agent on a cloud browser (no Chrome to install; works in Docker, CI, and serverless):
Set BROWSER_USE_API_KEY (get a key), then uncomment the browser= line in agent.py and run it again:
agent = Agent(
task="Find the number of stars of the browser-use repo", llm=llm, browser=Browser(use_cloud=True), )
Cloud browsers cost $0.02 per browser-hour plus network traffic (pricing), and add stealth, residential proxies, CAPTCHA solving, and a live view URL. Same code, no other changes.
Maintained by Browser Use. Compatible with Claude.
Use Claude's browser toolset with Browser Use as the driver. Browser Use implements all 31 browser actions and can control a local browser, a Browser Use Cloud browser, or an existing remote browser over CDP. Bash is included in the Browser Use integration for processing data and writing files.
Requires an Anthropic SDK version that includes anthropic.tools.browser. Bash requires a Linux or macOS host with /bin/bash; use WSL on Windows. The snippet below runs inside an async function; see the quickstart for a complete script.
import os
from anthropic import AsyncAnthropic from browser_use.integrations.toolsets_for_claude import Bash, BrowserUse
task = 'Open example.com and report its page title.' driver = BrowserUse() # Or BrowserUse(use_cloud=True) bash = Bash(output_dir='outputs')
async with driver, AsyncAnthropic() as client: runner = client.beta.messages.tool_runner( model=os.environ['ANTHROPIC_MODEL'], max_tokens=32_768, max_iterations=100, tools=[driver, bash], messages=[{'role': 'user', 'content': task}], ) result = await runner.until_done()
Quickstart ↗ · Integration docs ↗
This very hard benchmark targets the hardest browser tasks. On easier tasks, even smaller models can achieve very high success rates. Results shown are from a 60-task subset of BU Bench V2.
Should I use the fully hosted cloud, CLI, or Python library?
The CLI and Python library can each connect to a local or cloud browser. A cloud browser hosts the browser; the fully hosted API runs the agent as well.
What's the best model to use?
We recommend BU2, our model optimized for browser automation: ChatBrowserUse(model='bu-2-0'). It uses BROWSER_USE_API_KEY; ChatBrowserUse() currently selects the same model.
The best choice depends on your tasks, latency, and budget. See the BU2 model card, benchmark, and supported models and pricing to compare options.
Can I use Claude / GPT / Gemini through ChatBrowserUse?
Yes. ChatBrowserUse accepts provider-prefixed model IDs through the