mcp-server-search
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An MCP server providing Google search functionality for AI models, enabling them to access up-to-date web information.
MCP Server Search
An MCP (Model Context Protocol) server that provides Google search functionality for AI models. This server allows models to search for up-to-date information from the web.
Features
- Google search integration with caching
- Configurable request delays and retries to avoid rate limiting
- Support for both simple and advanced searches (with descriptions)
- Throttling and randomization to be a good web citizen
Installation
Using Docker (Recommended)
-
Build the Docker image:
docker build -t mcp-server-search . -
Create required directories for persistence:
mkdir -p ./logs ./cache -
Run the container (with SSE enabled):
docker run --rm -p 8000:8000 \ -v "$(pwd)/logs:/app/logs" \ -v "$(pwd)/cache:/app/cache" \ mcp-server-search
This will start the server with SSE enabled and make it accessible at http://localhost:8000/sse.
The volumes ensure:
- Logs are persisted to
./logsdirectory - Search cache is persisted to
./cachedirectory - Both directories are automatically created by Docker if they don't exist
Note: The -i flag is required for MCP protocol communication, and --rm automatically removes the container when it exits.
Cline Integration
To use this MCP server with Cline, add the following configuration to your Cline MCP settings file (located at ~/.config/Code/User/globalStorage/rooveterinaryinc.roo-cline/settings/cline_mcp_settings.json for VS Code):
{
"mcpServers": {
"google_search": {
"url": "http://localhost:8000/sse"
}
}
}
This configuration:
- Connects to the search MCP server via HTTP SSE on port 8000 at the
/sseendpoint - No longer uses the Docker stdio transport; Cline connects directly to the HTTP endpoint
Configuration
The server accepts the following command-line arguments:
--log-level: Set the logging level (DEBUG, INFO, WARNING, ERROR, CRITICAL). Default: INFO--log-file: Path to log file (default: stdout)--cache-path: Path to the search cache file (default: cache/google_cache.db)--request-delay: Delay between search requests in seconds (default: 5)--max-retries: Maximum number of retries for failed searches (default: 3)
Usage
The server exposes the following MCP endpoints:
Tools
-
google_search: Search Google and return results. Results are presented in a formatted Markdown structure with titles, URLs, and descriptions (when enabled).Parameters:
query(string, required): The search query to executenum_results(integer, optional): Number of results to return (min: 1, max: 20, default: 5)use_cache(boolean, optional): Whether to use cached results if available (default: true)include_descriptions(boolean, optional): Whether to include descriptions in results (default: true)
Features:
- Automatic request throttling and retry mechanism
- Random user agent rotation for better request distribution
- File-based caching with thread-safe access
- Exponential backoff on rate limiting (HTTP 429)
Prompts
-
google_search: Search Google with the given query. Returns results in a conversational format.Parameters:
query(string, required): The search query to executenum_results(integer, optional): Number of results to return (1-20, default: 5)
About MCP
The Model Context Protocol (MCP) is a protocol for connecting Large Language Models (LLMs) with tools and data sources. Learn more at github.com/modelcontextprotocol.
