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:

docker run --rm -i \
  -v "$(pwd)/logs:/app/logs" \
  -v "$(pwd)/cache:/app/cache" \
  mcp-server-search

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):

{
    "mcpServers": {
        "google_search": {
            "command": "docker",
            "args": [
                "run",
                "--rm",
                "-i",
                "mcp-server-search"
            ],
            "disabled": false,
            "alwaysAllow": []
        }
    }
}

This configuration:

Sets up the search MCP server to run in a Docker container
Uses the --rm flag to automatically remove the container when it exits
Uses -i for interactive mode required by the MCP protocol
Disables the server by default for security (set disabled to false to enable)
Requires explicit approval for all tool uses (alwaysAllow is empty)

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.