Browser Use
Browser agents and stealth cloud browsers for AI: run web tasks, fill forms, extract data.
作者提供的说明(英文原文)
220 browser automation tools for Chrome, Edge, and Firefox via CDP + BiDi. 100% Python.
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。
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 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"wavexis": {
"command": "uvx",
"args": [
"wavexis-mcp"
]
}
}
}在终端中运行这条命令
claude mcp add wavexis -- uvx wavexis-mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"wavexis": {
"command": "uvx",
"args": [
"wavexis-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": {
"wavexis": {
"type": "stdio",
"command": "uvx",
"args": [
"wavexis-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。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
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。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
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7日
注册名称已通过 GitHub 账户 MathiasPaulenko 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
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 1 项适用的基础检查中通过了 1 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。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(1.6.24)于3个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。
同一分类中有:Browser Use, Chrome DevTools MCP, MCP Server Browser
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
Browser agents and stealth cloud browsers for AI: run web tasks, fill forms, extract data.
MCP server for Chrome DevTools
MCP server for browser use access
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。
MCP server — 220 browser automation tools for LLMs
Chrome + Firefox · CDP + BiDi · 100% Python · zero Node.js · zero Chromium download
English | 简体中文 | 日本語
MCP server that exposes the wavexis browser automation library to LLMs. 220 tools across 13 capability tiers. No Node.js, no Chromium download — uses your existing Chrome/Edge. 100% Python.
30 seconds to your first screenshot. Add this to your MCP client config (Claude Desktop, Cursor, Windsurf, VS Code):
{
"mcpServers": { "wavexis": { "command": "uvx", "args": ["wavexis-mcp", "--caps", "all"] } } }
Then ask your LLM:
*"Take a full-page screenshot of https://example.com"*
The LLM calls wavexis_screenshot(url="https://example.com", full_page=true) and returns the screenshot. No Node.js, no Chromium download, no setup beyond the config above.
WaveXisMCP wraps the wavexis browser automation library and exposes it as an MCP server. You don't need Node.js, Playwright, or a separate Chromium download — WaveXisMCP launches your existing Chrome or Edge installation directly.
--caps. Start with core (72 tools), add tiers as neededstealth=true hides navigator.webdriver, fakes plugins/languages/chrome runtimesuggestion field so the LLM self-corrects without human helpYou (natural language)
→ LLM decides which tool to call → WaveXisMCP receives the tool call → wavexis library executes it via CDP or BiDi → Chrome/Edge/Firefox performs the action ← Result returned as JSON (text, base64, file path) ← JSON passed back to LLM ← LLM summarizes the result for you
The LLM never sees the browser directly. It only sees tool definitions (name, description, parameters) and JSON responses. This means any MCP-compatible LLM client works out of the box — no custom integrations needed.
url parameter. The browser launches, executes, and closes automatically.core (72 tools) to all (220 tools). Enable only what you need via --caps.suggestion field that tells the LLM what to do next, enabling self-correction without human intervention.pip install wavexis-mcp
The CDP backend (Chromium) is included by default. For the BiDi backend (Firefox):
pip install "wavexis-mcp[bidi]"
Or run without installing (recommended):
uvx wavexis-mcp
Add to your MCP client config (Claude Desktop, Cursor, Windsurf, VS Code):
{
"mcpServers": { "wavexis": { "command": "uvx", "args": ["wavexis-mcp", "--caps", "all"] } } }
Or with pip:
{
"mcpServers": { "wavexis": { "command": "wavexis-mcp", "args": ["--caps", "all"] } } }
Call any tool with a url parameter — the browser launches, executes, and closes automatically:
wavexis_screenshot(url="https://example.com", full_page=true)
Open a session, chain multiple actions, close when done:
wavexis_session_open(backend="cdp", headless=false)
→ {"session_id": "abc-123"}
wavexis_navigate(session_id="abc-123", url="https://example.com") wavexis_click(session_id="abc-123", selector="#login") wavexis_screenshot(session_id="abc-123") wavexis_session_close(session_id="abc-123")
Use wavexis_act to interact with pages using natural language:
wavexis_session_open(backend="cdp")
wavexis_navigate(session_id="abc-123", url="https://example.com") wavexis_act(session_id="abc-123", instruction="click the login button") → {"action": "click", "element": {"ref": "el-3", "role": "button", "name": "Login"}, "status": "ok"}
The wavexis_act tool takes an a11y snapshot, matches the instruction to an element using keyword scoring, and executes the detected action (click, type, fill, hover). No external LLM calls — pure heuristic matching.
| Tier | Flag | Tools | Key features |
|---|---|---|---|
| Core | always on | 72 | Session, navigation, screenshot, PDF, scrape, eval, DOM, input, cookies, tabs, NL interaction, iframe, shadow DOM, events |
| Network | --caps=network | 20 | Headers, UA, block, throttle, cache, HAR, intercept, mock, modify req/resp, request body, replay HAR, request list |
| Storage | --caps=storage | 18 | localStorage, sessionStorage, cache storage, IndexedDB, state save/restore |
| Emulation | --caps=emulation | 9 | Device, viewport, geolocation, timezone, dark mode, locale, CPU, touch, sensors |
| A11y | --caps=a11y | 4 | Accessibility tree snapshot, node traversal, axe-core audit |
| Interactions | --caps=interactions | 5 | Dialogs, downloads, permissions |
| DevTools | --caps=devtools | 31 | Performance, CSS, debugging, overlay, console, security, window mgmt, combined trace, annotated screenshot |
| Vision | --caps=vision | 7 | Coordinate-based mouse (pixel-precise) |
| Video | --caps=video | 4 | Video recording, chapters, action overlay |
| Testing | --caps=testing | 6 | Assertions, locator generation |
| Workflows | --caps=workflows | 6 | Multi-action YAML, raw CDP/BiDi, browser context CRUD |
| Data | --caps=data | 7 | Codegen, Lighthouse audit, extract, websocket intercept, crawl, visual diff, core web vitals |
| Experimental | --caps=experimental | 31 | Service workers, animations, WebAuthn, WebAudio, media, cast, bluetooth, extensions, prefs |
| Total | --caps=all | 220 |
Default: --caps=core (72 tools). Enable all: --caps=all. Enable specific: --caps=network,storage,emulation.
Tip: Start with
--caps coreand add tiers as needed. Each tier adds tool definitions to the LLM's context, which consumes tokens. For most tasks,core,network,storage(110 tools) is a good balance.
WaveXisMCP supports two backends with full feature parity:
pip install "wavexis-mcp[bidi]"Select per session:
# CDP (default, Chrome/Edge only)
wavexis_session_open(backend="cdp")
wavexis_session_open(backend="bidi", browser="chrome")
wavexis_session_open(backend="bidi", browser="firefox")
Use connect_existing=True to launch Chrome with --remote-debugging-port and connect to it. Useful for reusing a browser profile with logged-in sessions:
# Launch Chrome with debug port and connect via CDP
wavexis_session_open(connect_existing=true)
wavexis_session_open(connect_existing=true, user_data_dir="C:/Users/me/ChromeProfile")
Chrome is launched headed (headless is ignored). The browser subprocess is terminated when the session is closed.
Chain multiple actions in a single tool call by passing a YAML string:
wavexis_multi_action(
config=""" actions:
""", session_id="abc-123" )
Supported action types: navigate, screenshot, eval, click, type, fill. Set continue_on_error: true to keep executing on failures.
Resources (read-only browser state):
wavexis://session/{id}/url — current page URLwavexis://session/{id}/cookies — cookies as JSONwavexis://session/{id}/console — console messageswavexis://session/{id}/tabs — open tabsPrompts (workflow templates):
scrape_page(url, selector) — scrape and extract contentaudit_page(url) — full a11y + performance auditfill_form(url, fields) — fill a form on a pagedebug_page(url) — debug console, network, performanceRun WaveXisMCP as an HTTP server for CI/CD, shared instances, or Docker:
# HTTP on localhost
wavexis-mcp --transport http --port 8765
wavexis-mcp --transport http --port 8765 --caps all
wavexis-mcp --transport http --allow-remote --port 8765
Binds to 127.0.0.1 by default. Use `-
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