Google Search (via Chrome)▌
by cmann50
Integrate Google search with automated Chrome browsing for data extraction from web pages, perfect for web data scraping
Integrates Google search and webpage content extraction via Chrome browser automation, enabling access up-to-date web information for tasks like fact-checking and research.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Researchers needing current web information
- / Users requiring access to authenticated web content
- / Fact-checking and web research tasks
capabilities
- / Search Google with filtering by site and timeframe
- / Extract readable text content from webpages
- / Access authenticated content through your logged-in Chrome session
- / Get paginated search results with ~10 results per page
what it does
Performs Google searches and extracts webpage content by automating your Chrome browser. Uses Chrome's interface to avoid search blocking and access authenticated content.
about
Google Search (via Chrome) is a community-built MCP server published by cmann50 that provides AI assistants with tools and capabilities via the Model Context Protocol. Integrate Google search with automated Chrome browsing for data extraction from web pages, perfect for web data scraping It is categorized under search web. This server exposes 2 tools that AI clients can invoke during conversations and coding sessions.
how to install
You can install Google Search (via Chrome) in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Google Search (via Chrome) is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
MCP Chrome Google Search Tool
MCP tool for Google search and webpage content extraction using Chrome browser. Works with Claude to enable Google search and content fetching capabilities.
Quick Installation
-
Configure Claude Desktop
- Open Claude Desktop on Mac
- Go to Claude > Settings > Developer > Edit Config
- Add the following to your config file:
{ "mcpServers": { "mcp-chrome-google-search": { "command": "npx", "args": [ "-y", "@cmann50/mcp-chrome-google-search" ] } } }- Restart Claude Desktop
-
First Time Setup
-
Grant Accessibility Permissions
- On first run, approve macOS accessibility permissions prompt
- Navigate to: System Preferences > Security & Privacy > Privacy > Accessibility
- Add and enable permissions for your terminal app
-
Enable Chrome JavaScript from Apple Events
- Open Chrome
- Navigate to: View > Developer > Allow JavaScript from Apple Events
- One-time setup only
-
Once configured, Claude will be able to perform Google searches and extract webpage content through Chrome when you make requests.
Key Advantages
- Free to search google
- Opens and small windows and uses your chrome browser, so should not get blocked
- Since it is using your Chrome window it can access authenticated content. Claude can just open the URL in your browser.
Platform Support
- ✅ macOS
- ❌ Windows (not supported)
- ❌ Linux (not supported)
Requirements
- macOS
- Google Chrome
- Node.js 20 or higher
Alternative Installation Methods
NPX Installation
npx mcp-chrome-google-search
Custom Installation
- Checkout from git
- Run
npm run build - Add to Claude config (use absolute path):
{
"google-tools": {
"command": "node",
"args": [
"/your/checkout/path/mcp/mcp-chrome-google-search/dist/index.js"
]
}
}
Local development
To test changes locally bump package.json version and run to put it in edit mode:
npm install -g .
Then just do npm run build and the files will go in dist where claude is monitoring
Then press ctrl-R in claude desktop, no need to restart it
Debugging
Log Monitoring
# Follow logs in real-time
tail -n 20 -F ~/Library/Logs/Claude/mcp*.log
Dev Tools Access
- Enable developer settings:
echo '{"allowDevTools": true}' > ~/Library/Application\ Support/Claude/developer_settings.json
- Open DevTools: Command-Option-Shift-i in Claude desktop
- Use ctrl-r in Claude desktop while tailing for better errors
Troubleshooting
Chrome JavaScript Error
If you see:
execution error: Google Chrome got an error: Executing JavaScript through AppleScript
is turned off. For more information: https://support.google.com/chrome/?p=applescript (12)
Solution:
- Open Chrome
- View > Developer > Allow JavaScript from Apple Events
Accessibility Permission Issues
If Chrome control fails:
- Open System Preferences
- Security & Privacy > Privacy > Accessibility
- Ensure terminal app is listed and enabled
- Use lock icon to make changes if needed
Implementation Details
- Uses AppleScript for Chrome control
- Visible automation - Chrome windows will open/navigate
- Each request opens a new Chrome tab
- Close unused tabs periodically for optimal performance
- Only use with trusted Claude instances (has Chrome control access)
Support
- Create GitHub issues for problems
- Include macOS and Chrome version details
License
MIT License - see LICENSE file for details
FAQ
- What is the Google Search (via Chrome) MCP server?
- Google Search (via Chrome) is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Google Search (via Chrome)?
- This profile displays 28 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Web Research & Information Gathering
Fetch and extract information from websites automatically
Example
Research competitor pricing, scrape product reviews, monitor news mentions
Automate 5-10 hours/week of manual web research
Content Monitoring & Alerts
Track website changes, new content, price updates
Example
Monitor competitor blog for new posts, track stock availability, watch for pricing changes
Stay informed without manual checking, never miss important updates
Data Extraction & Aggregation
Extract structured data from multiple websites
Example
Compile product listings from 10 e-commerce sites, aggregate job postings, collect real estate data
Build datasets 100x faster than manual copying
API-less Integration
Interact with services that don't offer APIs
Example
Check form submissions, validate website functionality, test user flows
Automate interactions with any website, even without API
Implementation Guide▌
Prerequisites
- ›Claude Desktop or Cursor with MCP support
- ›Understanding of web scraping ethics and robots.txt
- ›Rate limiting awareness to avoid overwhelming target sites
- ›Knowledge of legal restrictions on data collection
Time Estimate
20-40 minutes including configuration and testing
Installation Steps
- 1.Install web automation MCP server via npm or pip
- 2.Configure allowed domains and rate limits in MCP config
- 3.Test with simple fetch: 'Get content from example.com'
- 4.Progress to extraction: 'Extract all product prices from this page'
- 5.Set up monitoring: 'Check this URL daily for changes'
- 6.Parse structured data: 'Create CSV from this table'
- 7.Respect robots.txt and rate limits always
Troubleshooting
- ⚠403 Forbidden: Website blocks bots—respect their wishes, use official API instead
- ⚠Rate limit errors: Slow down requests, add delays between fetches
- ⚠Stale data: Target site changed HTML structure—update selectors
- ⚠Timeout errors: Site is slow or blocking—increase timeout, try different user agent
- ⚠JavaScript-rendered content: Use headless browser MCP servers for dynamic sites
Best Practices▌
✓ Do
- +Check robots.txt and respect crawl rules
- +Rate limit requests: 1-2 requests/second maximum
- +Use official APIs when available instead of scraping
- +Identify your bot with descriptive user agent
- +Cache results to minimize repeated requests
- +Handle errors gracefully with retries and fallbacks
- +Validate extracted data for accuracy
✗ Don't
- −Don't scrape sites that explicitly forbid it (robots.txt, ToS)
- −Don't overwhelm servers with rapid requests—use rate limiting
- −Don't scrape personal data without consent and legal basis
- −Don't ignore copyright on extracted content
- −Don't assume HTML structure is stable—handle changes
- −Don't use scraped data for commercial purposes without permission
💡 Pro Tips
- ★Use CSS selectors or XPath for robust data extraction
- ★Set up monitoring alerts for extraction failures (structure changed)
- ★Implement exponential backoff for retries on failures
- ★Store raw HTML for reprocessing if extraction logic changes
- ★Combine with data analysis tools for insights from extracted data
- ★Consider using official APIs or RSS feeds as more stable alternatives
Technical Details▌
Architecture
MCP server handles HTTP requests, HTML parsing, JavaScript rendering (if headless browser), and returns structured data to Claude.
Protocols
- HTTP/HTTPS
- WebSocket (for real-time sites)
- Puppeteer/Playwright (for JavaScript sites)
Compatibility
- Static HTML sites
- JavaScript-rendered SPAs (with headless browser)
- REST APIs
- GraphQL endpoints
When to Use This▌
✓ Use When
Use for research automation, content monitoring, data aggregation from multiple sources, and when official APIs don't exist. Best for read-only information gathering.
✗ Avoid When
Avoid for sites with APIs (use API instead), sites that explicitly forbid scraping, when data is copyrighted, or for login-required content without proper authorization.
Integration▌
- →Scheduled monitoring with change detection
- →Multi-source data aggregation pipelines
- →Fallback to web scraping when API rate limits hit
- →Headless browser for JavaScript-heavy sites
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.5★★★★★28 reviews- ★★★★★Ira Okafor· Dec 28, 2024
Google Search (via Chrome) reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Ishan Thompson· Nov 19, 2024
Useful MCP listing: Google Search (via Chrome) is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Ishan Park· Oct 10, 2024
Google Search (via Chrome) is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Oshnikdeep· Sep 25, 2024
Google Search (via Chrome) is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Piyush G· Sep 21, 2024
Strong directory entry: Google Search (via Chrome) surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Nia Lopez· Sep 21, 2024
According to our notes, Google Search (via Chrome) benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Omar Gill· Sep 17, 2024
We wired Google Search (via Chrome) into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Ganesh Mohane· Aug 16, 2024
Useful MCP listing: Google Search (via Chrome) is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Shikha Mishra· Aug 12, 2024
Google Search (via Chrome) is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Maya Diallo· Aug 12, 2024
We wired Google Search (via Chrome) into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
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