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Cloud Spanner MCP Server

docs/SPANNER_README.md

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Cloud Spanner MCP Server

The Cloud Spanner Model Context Protocol (MCP) Server gives AI-powered development tools the ability to work with your Google Cloud Spanner databases. It supports executing SQL queries and exploring schemas.

Features

An editor configured to use the Cloud Spanner MCP server can use its AI capabilities to help you:

  • Query Data - Execute DML and DQL SQL queries
  • Explore Schema - List tables and view schema details

Prerequisites

  • Node.js installed.
  • A Google Cloud project with the Cloud Spanner API enabled.
  • Ensure Application Default Credentials are available in your environment.
  • IAM Permissions:
    • Cloud Spanner Database User (roles/spanner.databaseUser) (for data access)
    • Cloud Spanner Viewer (roles/spanner.viewer) (for schema access)

Install & Configuration

  1. In the Antigravity MCP Store, click the "Install" button.

    [!NOTE] On first use, the installation process automatically downloads and uses MCP Toolbox >=0.26.0. To update MCP Toolbox, use: npm i -g @toolbox-sdk/server@latest To always run the latest version, update the MCP server configuration to use: npx -y @toolbox-sdk/server@latest --prebuilt spanner.

  2. Add the required inputs for your instance in the configuration pop-up, then click "Save". You can update this configuration at any time in the "Configure" tab.

You'll now be able to see all enabled tools in the "Tools" tab.

[!NOTE] If you encounter issues with Windows Defender blocking the execution, you may need to configure an allowlist. See Configure exclusions for Microsoft Defender Antivirus for more details.

Usage

Once configured, the MCP server will automatically provide Cloud Spanner capabilities to your AI assistant. You can:

  • "Execute a DML query to update customer names."
  • "List all tables in the my-database."
  • "Execute a DQL query to select data from orders table."

Server Capabilities

The Cloud Spanner MCP server provides the following tools:

Tool NameDescription
execute_sqlUse this tool to execute DML SQL.
execute_sql_dqlUse this tool to execute DQL SQL.
list_tablesLists detailed schema information for user-created tables.
list_graphsLists detailed graph schema information for user-created graphs.

Custom MCP Server Configuration

The MCP server is configured using environment variables.

bash
export SPANNER_PROJECT="<your-gcp-project-id>"
export SPANNER_INSTANCE="<your-spanner-instance-id>"
export SPANNER_DATABASE="<your-spanner-database-id>"
export SPANNER_DIALECT="googlesql" # Optional: "googlesql" or "postgresql". Defaults to "googlesql".

Add the following configuration to your MCP client (e.g., settings.json for Gemini CLI, mcp_config.json for Antigravity):

json
{
  "mcpServers": {
    "spanner": {
      "command": "npx",
      "args": ["-y", "@toolbox-sdk/server", "--prebuilt", "spanner", "--stdio"],
      "env": {
        "SPANNER_PROJECT": "your-project-id",
        "SPANNER_INSTANCE": "your-instance-id",
        "SPANNER_DATABASE": "your-database-name",
        "SPANNER_DIALECT": "googlesql"
      }
    }
  }
}

Documentation

For more information, visit the Cloud Spanner documentation.