Browser Use
Lets AI do web tasks for you, such as filling forms, searching and extracting data, in the maker’s cloud browsers or on your computer.
Description from the maker (original English)
220 browser automation tools for Chrome, Edge, and Firefox via CDP + BiDi. 100% Python.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
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Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"wavexis": {
"command": "uvx",
"args": [
"wavexis-mcp"
]
}
}
}Run this in your terminal
claude mcp add wavexis -- uvx wavexis-mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"wavexis": {
"command": "uvx",
"args": [
"wavexis-mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"wavexis": {
"type": "stdio",
"command": "uvx",
"args": [
"wavexis-mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
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These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account MathiasPaulenko, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (1.6.24) reached the registry 3 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: Browser Use, Chrome DevTools MCP, MCP Server Browser
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Lets AI do web tasks for you, such as filling forms, searching and extracting data, in the maker’s cloud browsers or on your computer.
Lets AI use Chrome’s developer tools to inspect pages, find what makes them slow and spot errors. Made by the Chrome DevTools team.
MCP server for browser use access
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
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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