What is required to use Google Custom Search MCP?
You need a Google Cloud project with the Custom Search API enabled, a service account with a JSON key, and a Custom Search Engine ID. Environment variables authenticate the service account.
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Basic information
No overview available yet
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"google-search": {
"command": "uv",
"args": [
"run",
"path/to/your/clone/of/google-custom-search-mcp"
],
"env": {
"GOOGLE_SERVICE_ACCOUNT_FILE": "/path/to/your/service-account-key.json",
"GOOGLE_SEARCH_ENGINE_ID": "your-search-engine-id"
}
}
}
}Tool list not available yet
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We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Google Custom Search MCP is an async Python MCP (Model Context Protocol) server that provides access to Google Custom Search API using service account authentication. It is designed for developers and AI assistants that need to perform Google Custom Search queries programmatically through the MCP protocol.
Clone the repository, configure a Google Service Account and Custom Search Engine, then run uv run google-custom-search-mcp with the required environment variables GOOGLE_SERVICE_ACCOUNT_FILE or GOOGLE_SERVICE_ACCOUNT_BASE64 and GOOGLE_SEARCH_ENGINE_ID. The server supports STDIO mode (default) and HTTP mode (via --transport http). Docker and Helm deployments are available.
You need a Google Cloud project with the Custom Search API enabled, a service account with a JSON key, and a Custom Search Engine ID. Environment variables authenticate the service account.
Authentication uses a Google Service Account, either via a file path (local development) or a base64-encoded JSON string (CI/CD). API keys are deprecated.
The Google Custom Search API provides 100 free search queries per day. Additional queries require billing setup. Service accounts have the

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