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.
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x000D 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.x000D x000D
x000D - Advanced Google Search with filtering options (date, language, country, safe search)x000D - Detailed webpage content extraction and analysis_x000D_ - Batch webpage analysis for comparing multiple sources_x000D_ - Environment variable support for API credentials_x000D_ - Comprehensive error handling and user feedback_x000D_ - MCP-compliant interface for seamless integration with AI assistants_x000D_ x000D
x000D - Node.js (v16 or higher)x000D - Python (v3.8 or higher)x000D - Google Cloud Platform account_x000D_ - Custom Search Engine ID_x000D_ - Google API Key_x000D_ x000D
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1. Clone the repository:x000D
bash_x000D_
git clone https://github.com/your-username/google-search-mcp.git_x000D_
cd google-search-mcp_x000D_x000D
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2. Install Node.js dependencies:x000D
bash_x000D_
npm install_x000D_x000D
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3. Install Python dependencies:x000D
bash_x000D_
pip install flask google-api-python-client flask-cors beautifulsoup4 trafilatura markdownify_x000D_x000D
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4. Build the TypeScript code:x000D
bash_x000D_
npm run build_x000D_x000D
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5. Create a helper script to start the Python servers (Windows example):x000D
bash_x000D_
# Create start-python-servers.cmd_x000D_
@echo off_x000D_
echo Starting Python servers for Google Search MCP..._x000D_
_x000D_
REM Start Python search server_x000D_
start "Google Search API" cmd /k "python google_search.py"_x000D_
_x000D_
REM Start Python link viewer_x000D_
start "Link Viewer" cmd /k "python link_view.py"_x000D_
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echo Python servers started. You can close this window._x000D_x000D
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You can provide Google API credentials in two ways:x000D
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1. Environment Variables (Recommended):x000D
- Set GOOGLE_API_KEY and GOOGLE_SEARCH_ENGINE_ID in your environment_x000D_
- The server will automatically use these values_x000D_
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2. Configuration File:x000D
- Create an api-keys.json file in the root directory:x000D
json_x000D_
{_x000D_
"api_key": "your-google-api-key",_x000D_
"search_engine_id": "your-custom-search-engine-id"_x000D_
}_x000D_x000D
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x000D Add the server configuration to your MCP settings file:x000D x000D
File location: %APPDATA%CodeUserglobalStoragesaoudrizwan.claude-devsettingscline_mcp_settings.jsonx000D
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json_x000D_
{_x000D_
"mcpServers": {_x000D_
"google-search": {_x000D_
"command": "C:Program Filesnodejsnode.exe",_x000D_
"args": ["C:pathtogoogle-search-mcpdistgoogle-search.js"],_x000D_
"cwd": "C:pathtogoogle-search-mcp",_x000D_
"env": {_x000D_
"GOOGLE_API_KEY": "your-google-api-key",_x000D_
"GOOGLE_SEARCH_ENGINE_ID": "your-custom-search-engine-id"_x000D_
},_x000D_
"disabled": false,_x000D_
"autoApprove": []_x000D_
}_x000D_
}_x000D_
}_x000D_x000D
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File location: %APPDATA%Claudeclaude_desktop_config.jsonx000D
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json_x000D_
{_x000D_
"mcpServers": {_x000D_
"google-search": {_x000D_
"command": "C:Program Filesnodejsnode.exe",_x000D_
"args": ["C:pathtogoogle-search-mcpdistgoogle-search.js"],_x000D_
"cwd": "C:pathtogoogle-search-mcp",_x000D_
"env": {_x000D_
"GOOGLE_API_KEY": "your-google-api-key",_x000D_
"GOOGLE_SEARCH_ENGINE_ID": "your-custom-search-engine-id"_x000D_
},_x000D_
"disabled": false,_x000D_
"autoApprove": []_x000D_
}_x000D_
}_x000D_
}_x000D_x000D
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1. First, start the Python servers using the helper script:x000D
bash_x000D_
start-python-servers.cmd_x000D_x000D
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2. Configure the MCP settings to run only the Node.js server:x000D
json_x000D_
{_x000D_
"command": "C:Program Filesnodejsnode.exe",_x000D_
"args": ["C:pathtogoogle-search-mcpdistgoogle-search.js"]_x000D_
}_x000D_x000D
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Start both the TypeScript and Python servers with a single command:x000D
bash_x000D_
npm run start:all_x000D_x000D
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Search Google and return relevant results from the web. This tool finds web pages, articles, and information on specific topics using Google's search engine.x000D
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typescript_x000D_
{_x000D_
"name": "google_search",_x000D_
"arguments": {_x000D_
"query": "your search query",_x000D_
"num_results": 5, // optional, default: 5, max: 10_x000D_
"date_restrict": "w1", // optional, restrict to past day (d1), week (w1), month (m1), year (y1)_x000D_
"language": "en", // optional, ISO 639-1 language code (en, es, fr, de, ja, etc.)_x000D_
"country": "us", // optional, ISO 3166-1 alpha-2 country code (us, uk, ca, au, etc.)_x000D_
"safe_search": "medium" // optional, safe search level: "off", "medium", "high"_x000D_
}_x000D_
}_x000D_x000D
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Extract and analyze content from a webpage, converting it to readable text. This tool fetches the main content while removing ads, navigation elements, and other clutter.x000D
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typescript_x000D_
{_x000D_
"name": "extract_webpage_content",_x000D_
"arguments": {_x000D_
"url": "https://example.com"_x000D_
}_x000D_
}_x000D_x000D
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Extract and analyze content from multiple webpages in a single request. Ideal for comparing information across different sources or gathering comprehensive information on a topic.x000D
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typescript_x000D_
{_x000D_
"name": "extract_multiple_webpages",_x000D_
"arguments": {_x000D_
"urls": [_x000D_
"https://example1.com",_x000D_
"https://example2.com"_x000D_
]_x000D_
}_x000D_
}_x000D_x000D
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x000D Here are some examples of how to use the Google Search MCP tools:x000D x000D
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Search for information about artificial intelligence_x000D_x000D
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Search for recent news about climate change from the past week in Spanish_x000D_x000D
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Extract the content from https://example.com/article_x000D_x000D
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Compare information from these websites:_x000D_
- https://site1.com/topic_x000D_
- https://site2.com/topic_x000D_
- https://site3.com/topic_x000D_x000D
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1. Go to the Google Cloud Consolex000D
2. Create a new project or select an existing one_x000D_
3. Enable the Custom Search API_x000D_
4. Create API credentials (API Key)x000D
5. Go to the Custom Search Engine page_x000D_
6. Create a new search engine and get your Search Engine ID_x000D_
7. Add these credentials to your api-keys.json file_x000D_
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x000D The server provides detailed error messages for:x000D - Missing or invalid API credentials_x000D_ - Failed search requests_x000D_ - Invalid webpage URLs_x000D_ - Network connectivity issues_x000D_ x000D
x000D The server consists of two main components:x000D 1. TypeScript MCP Server: Handles MCP protocol communication and provides the tool interface_x000D_ 2. Python Flask Server: Manages Google API interactions and webpage content analysis_x000D_ x000D
x000D MIT_x000D_