A TypeScript-based MCP server that provides web search and webpage scraping capabilities using the Serper API. This server integrates with Claude Desktop to enable powerful web search and content extraction features.
Enhanced MCP server for advanced Google search with comprehensive operator support, crafted by Pavel Sukhachev (pashvc).
👋 Open for Opportunities!
I'm actively seeking new opportunities and collaborations. If you have interesting projects or job opportunities, feel free to reach out!
📧 Contact: pashvc@gmail.com
-
google_search
- Perform advanced Google searches with full operator support- Rich search results including organic results, knowledge graph, "people also ask", and related searches
- Supports region (default: 'us') and language (default: 'en') targeting
- Advanced search operators directly in the query:
-
" "
: Exact phrase matching -
site:
: Limit to specific domain (e.g.,site:linkedin.com/in/
for people) -
-
: Exclude terms (e.g.,-spam -ads
) -
OR
or|
: Alternative terms -
filetype:
orext:
: Specific file types -
intitle:
/allintitle:
: Words in page title -
inurl:
/allinurl:
: Words in URL -
before:
/after:
: Date filtering (YYYY-MM-DD format) -
*
: Wildcard for any word -
#..#
: Number ranges -
related:
: Find similar sites -
AROUND(X)
: Proximity search
-
-
scrape
- Extract content from web pages- Get plain text and optional markdown content
- Includes JSON-LD and head metadata
- Preserves document structure
# Find people
site:linkedin.com/in/ "data scientist" Python "San Francisco"
site:linkedin.com/in/ "software engineer" (Google OR Meta) -recruiter
# Find companies
site:linkedin.com/company/ fintech "series B"
site:linkedin.com/company/ "artificial intelligence" healthcare
# Stack Overflow solutions
site:stackoverflow.com "TypeError" pandas dataframe
# GitHub repositories
site:github.com "machine learning" README.md stars:>100
# Documentation
site:docs.python.org asyncio tutorial
# Research papers
filetype:pdf "deep learning" medical after:2023-01-01
site:arxiv.org "transformer architecture" "computer vision"
# Academic content
site:edu "climate change" research "peer reviewed"
# Exclude noise
python tutorial -youtube -video -course -udemy
# Multiple sites
(site:github.com OR site:gitlab.com) "react hooks" example
# Date and type filters
"machine learning" news after:2024-01-01 -opinion -sponsored
- Node.js >= 18
- Serper API key (set as
SERPER_API_KEY
environment variable)
Install dependencies:
npm install
Build the server:
npm run build
For development with auto-rebuild:
npm run watch
Run tests:
npm test # Run all tests
npm run test:watch # Run tests in watch mode
npm run test:coverage # Run tests with coverage
npm run test:integration # Run integration tests
Create a .env
file in the root directory:
SERPER_API_KEY=your_api_key_here
Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:
npm run inspector
The Inspector will provide a URL to access debugging tools in your browser.
To install Serper Search and Scrape for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @pashvc/mcp-server-serper --client claude
Add the server config at:
- MacOS:
~/Library/Application Support/Claude/claude_desktop_config.json
- Windows:
%APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"serper-search": {
"command": "npx",
"args": ["-y", "serper-search-scrape-mcp-server"],
"env": {
"SERPER_API_KEY": "your_api_key_here"
}
}
}
}
- Open the Cline extension settings
- Open "MCP Servers" tab
- Click on "Configure MCP Servers"
- Add the server config:
{
"mcpServers": {
"github.com/pashvc/mcp-server-serper": {
"command": "npx",
"args": ["-y", "serper-search-scrape-mcp-server"],
"env": {
"SERPER_API_KEY": "your_api_key_here"
},
"disabled": false,
"autoApprove": ["google_search", "scrape"]
}
}
}
Additional Cline configuration options:
-
disabled
: Set tofalse
to enable the server -
autoApprove
: List of tools that don't require explicit approval for each use
- Open the Cursor settings
- Open "Features" settings
- In the "MCP Servers" section, click on "Add new MCP Server"
- Choose a name, and select "command" as "Type"
- In the "Command" field, enter the following:
env SERPER_API_KEY=your_api_key_here npx -y serper-search-scrape-mcp-server
You can also run the server using Docker. First, build the image:
docker build -t mcp-server-serper .
Then run the container with your Serper API key:
docker run -e SERPER_API_KEY=your_api_key_here mcp-server-serper
Alternatively, if you have your environment variables in a .env
file:
docker run --env-file .env mcp-server-serper
For development, you might want to mount your source code as a volume:
docker run -v $(pwd):/app --env-file .env mcp-server-serper
Note: Make sure to replace your_api_key_here
with your actual Serper API key.