agentleFS
pencil20388-engpencil20388-eng/browser-automation-skills/skills/chrome-devtools-mcp-adspower/SKILL.md

chrome-devtools-mcp-adspower

Skill5 starsChanged 6 months agoMITView on GitHub

Connect Google's Chrome DevTools MCP to AdsPower antidetect browser profiles. This lets AI coding agents (Claude Code, Cursor, Codex CLI) control fingerprint-isolated browser sessions through natural language. AdsPower's Local API opens browser profiles and exposes a Chrome DevTools Protocol (CDP) endpoint for each one. Chrome DevTools MCP connects to that endpoint via --browserUrl. The ws_endpoint looks like: ws://127.0.0.1:XXXXX/devtools/browser/GUID Once the profile is open and you have the debug port, connect Chrome DevTools MCP: Replace XXXXX with the actual port from…

  • Reads credentials
  • Installs packages

The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈0

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Add to your MCP config (.claude/mcp.json or settings.json):

    line 74

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Chrome DevTools MCP + AdsPower Integration Skill

Connect Google's Chrome DevTools MCP to AdsPower antidetect browser profiles. This lets AI coding agents (Claude Code, Cursor, Codex CLI) control fingerprint-isolated browser sessions through natural language.

Why This Combination

  • Chrome DevTools MCP gives AI agents eyes in the browser: inspect DOM, monitor network, run JavaScript, take screenshots
  • AdsPower gives each browser session a unique fingerprint, proxy, and identity
  • Together: your AI agent can operate across multiple isolated browser identities — each with its own fingerprint, cookies, and IP address
Claude Code → Chrome DevTools MCP → AdsPower Profile (unique fingerprint + proxy)
                                  → AdsPower Profile (unique fingerprint + proxy)
                                  → AdsPower Profile (unique fingerprint + proxy)

How It Works

AdsPower's Local API opens browser profiles and exposes a Chrome DevTools Protocol (CDP) endpoint for each one. Chrome DevTools MCP connects to that endpoint via --browserUrl.

Prerequisites

  • AdsPower installed and running (paid plan with API access)
  • Chrome DevTools MCP installed (npm install -g chrome-devtools-mcp@latest)
  • API Key generated (AdsPower → Automation → API → Generate)
  • Python 3.8+ with requests installed

Step 1: Open an AdsPower Profile and Get the CDP Endpoint

import requests

API_KEY = "your_api_key"
BASE_URL = "http://local.adspower.net:50325"
HEADERS = {"Authorization": f"Bearer {API_KEY}"}

PROFILE_ID = "your_profile_id"

# Open the browser profile
resp = requests.get(
    f"{BASE_URL}/api/v1/browser/start?user_id={PROFILE_ID}",
    headers=HEADERS,
    timeout=30,
).json()

if resp["code"] == 0:
    # This is the CDP WebSocket endpoint
    ws_endpoint = resp["data"]["ws"]["puppeteer"]
    debug_port = ws_endpoint.split(":")[2].split("/")[0]
    print(f"CDP WebSocket: {ws_endpoint}")
    print(f"Debug port: {debug_port}")
else:
    print(f"Error: {resp['msg']}")

The ws_endpoint looks like: ws://127.0.0.1:XXXXX/devtools/browser/GUID

Step 2: Connect Chrome DevTools MCP to the AdsPower Profile

Once the profile is open and you have the debug port, connect Chrome DevTools MCP:

# Connect to the AdsPower browser instance
npx chrome-devtools-mcp@latest --browserUrl=http://127.0.0.1:XXXXX

Replace XXXXX with the actual port from Step 1.

Configure in Claude Code

Add to your MCP config (.claude/mcp.json or settings.json):

{
  "mcpServers": {
    "chrome-devtools": {
      "command": "npx",
      "args": [
        "-y",
        "chrome-devtools-mcp@latest",
        "--browserUrl=http://127.0.0.1:XXXXX"
      ]
    }
  }
}

Step 3: Use Natural Language to Control the Browser

Once connected, you can tell your AI agent:

> Navigate to amazon.com and check if the account is still logged in

> Take a screenshot of the current page

> Check the network requests for any blocked or failed calls

> Run document.title in the browser console and tell me what page this is

> Inspect the fingerprint by visiting browserscan.net

The AI agent sees the browser through Chrome DevTools MCP, while AdsPower ensures the browser has a unique fingerprint and proxy.

Automating Multiple Profiles

To work across multiple AdsPower profiles sequentially:

import requests
import subprocess
import time

API_KEY = "your_api_key"
BASE_URL = "http://local.adspower.net:50325"
HEADERS = {"Authorization": f"Bearer {API_KEY}"}

def get_profiles(group_name):
    resp = requests.get(
        f"{BASE_URL}/api/v1/user/list",
        headers=HEADERS,
        params={"group_name": group_name, "page": 1, "page_size": 100},
    ).json()
    return resp["data"]["list"]

def open_profile(profile_id):
    resp = requests.get(
        f"{BASE_URL}/api/v1/browser/start?user_id={profile_id}",
        headers=HEADERS,
        timeout=30,
    ).json()
    if resp["code"] == 0:
        ws = resp["data"]["ws"]["puppeteer"]
        port = ws.split(":")[2].split("/")[0]
        return port
    return None

def close_profile(profile_id):
    requests.get(
        f"{BASE_URL}/api/v1/browser/stop?user_id={profile_id}",
        headers=HEADERS,
    )

# Process each profile
profiles = get_profiles("My Campaign")
for p in profiles:
    port = open_profile(p["user_id"])
    if port:
        print(f"Profile {p['name']} ready on port {port}")
        print(f"Connect MCP: npx chrome-devtools-mcp@latest --browserUrl=http://127.0.0.1:{port}")
        # Your automation here...
        input("Press Enter when done with this profile...")
        close_profile(p["user_id"])
        time.sleep(2)

Use Cases

ScenarioWhat happens
Multi-account health checkOpen each profile → MCP checks login status, screenshots dashboard
Ad verificationOpen profiles with different geo proxies → MCP inspects ad content per region
Fingerprint auditingOpen profiles → MCP navigates to BrowserScan → reads fingerprint results
Authenticated scrapingOpen profile with saved cookies → MCP extracts data from logged-in pages
A/B test across identitiesOpen multiple profiles → MCP captures different UI versions

Important Notes

  • Each AdsPower profile exposes its own CDP port — you can only connect one MCP instance per profile at a time
  • Close the MCP connection before closing the AdsPower profile to avoid orphaned processes
  • The CDP port changes every time a profile is opened — always read it fresh from the API response
  • AdsPower handles fingerprint and proxy; Chrome DevTools MCP handles browser control and inspection
  • Rate limit: wait 1-2 seconds between opening/closing profiles

Resources

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.