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Mixelpixx Googlesearch Mcpserver
What is Mixelpixx Googlesearch Mcpserver
mixelpixx_GoogleSearch_McpServer is an MCP (Model Context Protocol) server that enables AI models to perform Google searches and analyze webpage content programmatically. It integrates Google Custom Search capabilities and provides tools for webpage content analysis.
Use cases
Use cases include performing automated Google searches, extracting and analyzing content from specific webpages, and conducting batch analysis of multiple webpages for research or data collection purposes.
How to use
To use mixelpixx_GoogleSearch_McpServer, clone the repository, install the necessary Node.js and Python dependencies, configure your Google API credentials in the ‘api-keys.json’ file, and run the server using the provided commands.
Key features
Key features include Google Custom Search integration, webpage content analysis, batch webpage analysis, and an MCP-compliant interface for seamless interaction with AI models.
Where to use
mixelpixx_GoogleSearch_McpServer can be used in fields such as AI development, web scraping, data analysis, and any application requiring automated Google search and content analysis.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Mixelpixx Googlesearch Mcpserver
mixelpixx_GoogleSearch_McpServer is an MCP (Model Context Protocol) server that enables AI models to perform Google searches and analyze webpage content programmatically. It integrates Google Custom Search capabilities and provides tools for webpage content analysis.
Use cases
Use cases include performing automated Google searches, extracting and analyzing content from specific webpages, and conducting batch analysis of multiple webpages for research or data collection purposes.
How to use
To use mixelpixx_GoogleSearch_McpServer, clone the repository, install the necessary Node.js and Python dependencies, configure your Google API credentials in the ‘api-keys.json’ file, and run the server using the provided commands.
Key features
Key features include Google Custom Search integration, webpage content analysis, batch webpage analysis, and an MCP-compliant interface for seamless interaction with AI models.
Where to use
mixelpixx_GoogleSearch_McpServer can be used in fields such as AI development, web scraping, data analysis, and any application requiring automated Google search and content analysis.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
Google Search MCP Server
An MCP (Model Context Protocol) server that provides Google search capabilities and webpage content analysis tools. This server enables AI models to perform Google searches and analyze webpage content programmatically.
Features
- Google Custom Search integration
- Webpage content analysis
- Batch webpage analysis
- MCP-compliant interface
Prerequisites
- Node.js (v16 or higher)
- Python (v3.8 or higher)
- Google Cloud Platform account
- Custom Search Engine ID
- Google API Key
Installation
- Clone the repository
- Install Node.js dependencies:
npm install
- Install Python dependencies:
pip install flask google-api-python-client flask-cors
Configuration
- Create a
api-keys.jsonfile in the root directory with your Google API credentials:
{
"api_key": "your-google-api-key",
"search_engine_id": "your-custom-search-engine-id"
}
- Add the server configuration to your MCP settings file (typically located at
%APPDATA%/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json):
{
"mcpServers": {
"google-search": {
"command": "npm",
"args": [
"run",
"start:all"
],
"cwd": "/path/to/google-search-server"
}
}
}
Building
npm run build
Running
Start both the TypeScript and Python servers:
npm run start:all
Or run them separately:
- TypeScript server:
npm start - Python servers:
npm run start:python
Available Tools
1. search
Perform Google searches and retrieve results.
{
"name": "search",
"arguments": {
"query": "your search query",
"num_results": 5 // optional, default: 5
}
}
2. analyze_webpage
Extract and analyze content from a single webpage.
{
"name": "analyze_webpage",
"arguments": {
"url": "https://example.com"
}
}
3. batch_analyze_webpages
Analyze multiple webpages in a single request.
{
"name": "batch_analyze_webpages",
"arguments": {
"urls": [
"https://example1.com",
"https://example2.com"
]
}
}
Getting Google API Credentials
- Go to the Google Cloud Console
- Create a new project or select an existing one
- Enable the Custom Search API
- Create API credentials (API Key)
- Go to the Custom Search Engine page
- Create a new search engine and get your Search Engine ID
- Add these credentials to your
api-keys.jsonfile
Error Handling
The server provides detailed error messages for:
- Missing or invalid API credentials
- Failed search requests
- Invalid webpage URLs
- Network connectivity issues
Architecture
The server consists of two main components:
- TypeScript MCP Server: Handles MCP protocol communication and provides the tool interface
- Python Flask Server: Manages Google API interactions and webpage content analysis
License
MIT
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.










