mcp-server-search

# 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) 1. Build the Docker image: ``` docker build -t mcp-server-search . ``` 2. Create required directories for persistence: ``` mkdir -p ./logs ./cache ``` 3. 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 `./logs` directory - Search cache is persisted to `./cache` directory - 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): ```json { "mcpServers": { "google_search": { "url": "http://localhost:8000/sse" } } } ``` This configuration: - Connects to the search MCP server via HTTP SSE on port 8000 at the `/sse` endpoint - 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 execute - `num_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 execute - `num_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](https://github.com/modelcontextprotocol).