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Serper (Google Search)

garylab

by garylab

Serper enables AI to access Google Search results via a powerful Google Search API, supporting location, language, and t

Enables AI to perform Google searches via the Serper API with support for location, language, and time period filters.

github stars

28

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Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

12+ specialized search typesLocation and language filteringIncludes Google Lens visual search

best for

  • / AI assistants needing current web information
  • / Research and fact-checking workflows
  • / Content creation requiring up-to-date data
  • / Academic research and citation finding

capabilities

  • / Perform Google web searches with filters
  • / Search Google Images, videos, and news
  • / Find places and maps information
  • / Search Google Scholar and patents
  • / Get shopping results and reviews
  • / Scrape webpage content

what it does

Provides Google search capabilities to AI through the Serper API with filtering options for location, language, and time periods. Includes specialized searches for images, news, shopping, academic papers, and more.

about

Serper (Google Search) is a community-built MCP server published by garylab that provides AI assistants with tools and capabilities via the Model Context Protocol. Serper enables AI to access Google Search results via a powerful Google Search API, supporting location, language, and t It is categorized under search web.

how to install

You can install Serper (Google Search) 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

Serper (Google Search) is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Serper MCP Server

PyPI version PyPI Downloads Monthly Downloads Python Version

A Model Context Protocol server that provides Google Search via Serper. This server enables LLMs to get search result information from Google.

Available Tools

Usage

Installing via Smithery

To install Serper MCP Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @garylab/serper-mcp-server --client claude

Using uv (recommended)

  1. Make sure you had installed uv on your os system.

  2. In your MCP client code configuration or Claude settings (file claude_desktop_config.json) add serper mcp server:

    {
        "mcpServers": {
            "serper": {
                "command": "uvx",
                "args": ["serper-mcp-server"],
                "env": {
                    "SERPER_API_KEY": "<Your Serper API key>"
                }
            }
        }
    }
    

    uv will download mcp server automatically using uvx from pypi.org and apply to your MCP client.

Using pip for project

  1. Add serper-mcp-server to your MCP client code requirements.txt file.

    serper-mcp-server
    
  2. Install the dependencies.

    pip install -r requirements.txt
    
  3. Add the configuration for you client:

    {
        "mcpServers": {
            "serper": {
                "command": "python3",
                "args": ["-m", "serper_mcp_server"],
                "env": {
                    "SERPER_API_KEY": "<Your Serper API key>"
                }
            }
        }
    }
    

Using pip for globally usage

  1. Make sure the pip or pip3 is in your os system.

    pip install serper-mcp-server
    # or
    pip3 install serper-mcp-server
    
  2. MCP client code configuration or Claude settings, add serper mcp server:

    {
        "mcpServers": {
            "serper": {
                "command": "python3",
                "args": ["serper-mcp-server"],
                "env": {
                    "SERPER_API_KEY": "<Your Serper API key>"
                }
            }
        }
    }
    

Debugging

You can use the MCP inspector to debug the server. For uvx installations:

npx @modelcontextprotocol/inspector uvx serper-mcp-server

Or if you've installed the package in a specific directory or are developing on it:

git clone https://github.com/garylab/serper-mcp-server.git
cd serper-mcp-server
npx @modelcontextprotocol/inspector uv run serper-mcp-server -e SERPER_API_KEY=<the key>

License

serper-mcp-server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.

FAQ

What is the Serper (Google Search) MCP server?
Serper (Google Search) 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 Serper (Google Search)?
This profile displays 34 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 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. 1.Install web automation MCP server via npm or pip
  2. 2.Configure allowed domains and rate limits in MCP config
  3. 3.Test with simple fetch: 'Get content from example.com'
  4. 4.Progress to extraction: 'Extract all product prices from this page'
  5. 5.Set up monitoring: 'Check this URL daily for changes'
  6. 6.Parse structured data: 'Create CSV from this table'
  7. 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

4.734 reviews
  • Xiao Harris· Dec 28, 2024

    Serper (Google Search) is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Ganesh Mohane· Dec 12, 2024

    Strong directory entry: Serper (Google Search) surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Shikha Mishra· Dec 8, 2024

    According to our notes, Serper (Google Search) benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Charlotte Mensah· Nov 19, 2024

    Useful MCP listing: Serper (Google Search) is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Sakshi Patil· Nov 3, 2024

    Serper (Google Search) is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Chaitanya Patil· Oct 22, 2024

    We evaluated Serper (Google Search) against two servers with overlapping tools; this profile had the clearer scope statement.

  • Amina Rahman· Oct 10, 2024

    Serper (Google Search) reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Daniel Gupta· Sep 13, 2024

    Serper (Google Search) is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Alexander Flores· Sep 1, 2024

    I recommend Serper (Google Search) for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Ira Shah· Sep 1, 2024

    Serper (Google Search) reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

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