mcp-google-search
by
What is mcp-google-search
mcp-google-server A MCP Server for Google Custom Search and Webpage Reading
A Model Context Protocol server that provides web search capabilities using Google Custom Search API and webpage content extraction functionality.
Setup
Getting Google API Key and Search Engine ID
-
Create a Google Cloud Project:
- Go to Google Cloud Console
- Create a new project or select an existing one
- Enable billing for your project
-
Enable Custom Search API:
- Go to API Library
- Search for "Custom Search API"
- Click "Enable"
-
Get API Key:
- Go to Credentials
- Click "Create Credentials" > "API Key"
- Copy your API key
- (Optional) Restrict the API key to only Custom Search API
-
Create Custom Search Engine:
- Go to Programmable Search Engine
- Enter the sites you want to search (use www.google.com for general web search)
- Click "Create"
- On the next page, click "Customize"
- In the settings, enable "Search the entire web"
- Copy your Search Engine ID (cx)
Development
Install dependencies:
npm install
Build the server:
npm run build
For development with auto-rebuild:
npm run watch
Features
Search Tool
Perform web searches using Google Custom Search API:
- Search the entire web or specific sites
- Control number of results (1-10)
- Get structured results with title, link, and snippet
Webpage Reader Tool
Extract content from any webpage:
- Fetch and parse webpage content
- Extract page title and main text
- Clean content by removing scripts and styles
- Return structured data with title, text, and URL
Installation
Installing via Smithery
To install Google Custom Search Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @adenot/mcp-google-search --client claude
To use with Claude Desktop, add the server config with your Google API credentials:
On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"google-search": {
"command": "npx",
"args": [
"-y",
"@adenot/mcp-google-search"
],
"env": {
"GOOGLE_API_KEY": "your-api-key-here",
"GOOGLE_SEARCH_ENGINE_ID": "your-search-engine-id-here"
}
}
}
}
Usage
Search Tool
{
"name": "search",
"arguments": {
"query": "your search query",
"num": 5 // optional, default is 5, max is 10
}
}
Webpage Reader Tool
{
"name": "read_webpage",
"arguments": {
"url": "https://example.com"
}
}
Example response from webpage reader:
{
"title": "Example Domain",
"text": "Extracted and cleaned webpage content...",
"url": "https://example.com"
}
Debugging
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.
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Frequently Asked Questions
What is MCP?
MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.
What are MCP Servers?
MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.
How do MCP Servers work?
MCP Servers follow a client-server architecture where a host application (like Claude Desktop) connects to multiple servers. Each server provides specific functionality through standardized endpoints and protocols, enabling Claude to access data and perform actions through the standardized protocol.
Are MCP Servers secure?
Yes, MCP Servers are designed with security in mind. They run locally with explicit configuration and permissions, require user approval for actions, and include built-in security features to prevent unauthorized access and ensure data privacy.
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