Provides browser automation and debugging capabilities through Chrome DevTools, enabling performance analysis, network inspection, automated interactions, and debugging of web applications running in Chrome
Uses Puppeteer for reliable browser automation, providing tools for navigation, form filling, clicking, screenshot capture, and waiting for page elements and events
Chrome DevTools MCP
chrome-devtools-mcp
lets your coding agent (such as Gemini, Claude, Cursor or Copilot)
control and inspect a live Chrome browser. It acts as a Model-Context-Protocol
(MCP) server, giving your AI coding assistant access to the full power of
Chrome DevTools for reliable automation, in-depth debugging, and performance analysis.
Tool reference | Changelog | Contributing | Troubleshooting
Key features
Get performance insights: Uses Chrome DevTools to record traces and extract actionable performance insights.
Advanced browser debugging: Analyze network requests, take screenshots and check the browser console.
Reliable automation. Uses puppeteer to automate actions in Chrome and automatically wait for action results.
Disclaimers
chrome-devtools-mcp
exposes content of the browser instance to the MCP clients
allowing them to inspect, debug, and modify any data in the browser or DevTools.
Avoid sharing sensitive or personal information that you don't want to share with
MCP clients.
Requirements
Node.js v20.19 or a newer latest maintenance LTS version.
Chrome current stable version or newer.
npm.
Getting started
Add the following config to your MCP client:
Using chrome-devtools-mcp@latest
ensures that your MCP client will always use the latest version of the Chrome DevTools MCP server.
MCP Client configuration
On Windows 11
Configure the Chrome install location and increase the startup timeout by updating .codex/config.toml
and adding the following env
and startup_timeout_ms
parameters:
Start Copilot CLI:
Start the dialog to add a new MCP server by running:
Configure the following fields and press CTR-S
to save the configuration:
Server name:
chrome-devtools
Server Type:
[1] Local
Command:
npx
Arguments:
-y, chrome-devtools-mcp@latest
Click the button to install:
Or install manually:
Go to Cursor Settings
-> MCP
-> New MCP Server
. Use the config provided above.
Project wide:
Globally:
Alternatively, follow the MCP guide and use the standard config from above.
Go to Settings | Tools | AI Assistant | Model Context Protocol (MCP)
-> Add
. Use the config provided above.
The same way chrome-devtools-mcp can be configured for JetBrains Junie in Settings | Tools | Junie | MCP Settings
-> Add
. Use the config provided above.
Click the button to install:
Go to Settings | AI | Manage MCP Servers
-> + Add
to add an MCP Server. Use the config provided above.
Your first prompt
Enter the following prompt in your MCP Client to check if everything is working:
Your MCP client should open the browser and record a performance trace.
The MCP server will start the browser automatically once the MCP client uses a tool that requires a running browser instance. Connecting to the Chrome DevTools MCP server on its own will not automatically start the browser.
Tools
If you run into any issues, checkout our troubleshooting guide.
Input automation (7 tools)
Navigation automation (7 tools)
Emulation (3 tools)
Performance (3 tools)
Network (2 tools)
Debugging (4 tools)
Configuration
The Chrome DevTools MCP server supports the following configuration option:
--browserUrl
Connect to a running Chrome instance using port forwarding. For more details see: https://developer.chrome.com/docs/devtools/remote-debugging/local-server.Type: string
--headless
Whether to run in headless (no UI) mode.Type: boolean
Default:
false
--executablePath
Path to custom Chrome executable.Type: string
--isolated
If specified, creates a temporary user-data-dir that is automatically cleaned up after the browser is closed.Type: boolean
Default:
false
--channel
Specify a different Chrome channel that should be used. The default is the stable channel version.Type: string
Choices:
stable
,canary
,beta
,dev
--logFile
Path to a file to write debug logs to. Set the env variableDEBUG
to*
to enable verbose logs. Useful for submitting bug reports.Type: string
--viewport
Initial viewport size for the Chrome instances started by the server. For example,1280x720
. In headless mode, max size is 3840x2160px.Type: string
--proxyServer
Proxy server configuration for Chrome passed as --proxy-server when launching the browser. See https://www.chromium.org/developers/design-documents/network-settings/ for details.Type: string
--acceptInsecureCerts
If enabled, ignores errors relative to self-signed and expired certificates. Use with caution.Type: boolean
Pass them via the args
property in the JSON configuration. For example:
You can also run npx chrome-devtools-mcp@latest --help
to see all available configuration options.
Concepts
User data directory
chrome-devtools-mcp
starts a Chrome's stable channel instance using the following user
data directory:
Linux / macOS:
$HOME/.cache/chrome-devtools-mcp/chrome-profile-$CHANNEL
Windows:
%HOMEPATH%/.cache/chrome-devtools-mcp/chrome-profile-$CHANNEL
The user data directory is not cleared between runs and shared across
all instances of chrome-devtools-mcp
. Set the isolated
option to true
to use a temporary user data dir instead which will be cleared automatically after
the browser is closed.
Known limitations
Operating system sandboxes
Some MCP clients allow sandboxing the MCP server using macOS Seatbelt or Linux
containers. If sandboxes are enabled, chrome-devtools-mcp
is not able to start
Chrome that requires permissions to create its own sandboxes. As a workaround,
either disable sandboxing for chrome-devtools-mcp
in your MCP client or use
--connect-url
to connect to a Chrome instance that you start manually outside
of the MCP client sandbox.
This server cannot be installed
local-only server
The server can only run on the client's local machine because it depends on local resources.
Enables AI coding assistants to control and inspect a live Chrome browser through Chrome DevTools. Provides browser automation, performance analysis, debugging capabilities, and network request monitoring.