# Cloud SQL for SQL Server MCP Server
The Cloud SQL for SQL Server Model Context Protocol (MCP) Server gives AI-powered development tools the ability to work with your Google Cloud SQL for SQL Server databases. It supports connecting to instances, exploring schemas, and running queries.
## Features
An editor configured to use the Cloud SQL for SQL Server MCP server can use its AI capabilities to help you:
- **Query Data** - Execute SQL queries
- **Explore Schema** - List tables and view schema details
For Cloud SQL infrastructure management, search the MCP store for the Cloud SQL for SQL Server Admin MCP Server.
## Prerequisites
* [Node.js](https://nodejs.org/) installed.
* A Google Cloud project with the **Cloud SQL Admin API** enabled.
* Ensure [Application Default Credentials](https://cloud.google.com/docs/authentication/gcloud) are available in your environment.
* IAM Permissions:
* Cloud SQL Client (`roles/cloudsql.client`)
> **Note:** If your instance uses private IPs, you must run the MCP server in the same Virtual Private Cloud (VPC) network.
## Install & Configuration
1. In the Antigravity MCP Store, click the "Install" button.
2. Add the required inputs for your [instance](https://cloud.google.com/sql/docs/sqlserver/instance-info) 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](https://learn.microsoft.com/en-us/microsoft-365/security/defender-endpoint/configure-exclusions-microsoft-defender-antivirus?view=o365-worldwide) for more details.
## Usage
Once configured, the MCP server will automatically provide Cloud SQL for SQL Server capabilities to your AI assistant. You can:
* "Select top 10 rows from the customers table."
* "List all tables in the database."
## Server Capabilities
The Cloud SQL for SQL Server MCP server provides the following tools:
| Tool Name | Description |
|:--------------|:-----------------------------------------------------------|
| `execute_sql` | Use this tool to execute SQL. |
| `list_tables` | Lists detailed schema information for user-created tables. |
## Custom MCP Server Configuration
The MCP server is configured using environment variables.
```bash
export CLOUD_SQL_MSSQL_PROJECT="<your-gcp-project-id>"
export CLOUD_SQL_MSSQL_REGION="<your-cloud-sql-region>"
export CLOUD_SQL_MSSQL_INSTANCE="<your-cloud-sql-instance-id>"
export CLOUD_SQL_MSSQL_DATABASE="<your-database-name>"
export CLOUD_SQL_MSSQL_USER="<your-database-user>" # Optional
export CLOUD_SQL_MSSQL_PASSWORD="<your-database-password>" # Optional
export CLOUD_SQL_MSSQL_IP_TYPE="PUBLIC" # Optional: `PUBLIC`, `PRIVATE`, `PSC`. Defaults to `PUBLIC`.
```
Add the following configuration to your MCP client (e.g., `settings.json` for Gemini CLI, `mcp_config.json` for Antigravity):
```json
{
"mcpServers": {
"cloud-sql-mssql": {
"command": "npx",
"args": ["-y", "@toolbox-sdk/server", "--prebuilt", "cloud-sql-mssql", "--stdio"],
"env": {
"CLOUD_SQL_MSSQL_PROJECT": "your-project-id",
"CLOUD_SQL_MSSQL_REGION": "your-region",
"CLOUD_SQL_MSSQL_INSTANCE": "your-instance-id",
"CLOUD_SQL_MSSQL_DATABASE": "your-database-name",
"CLOUD_SQL_MSSQL_USER": "your-username",
"CLOUD_SQL_MSSQL_PASSWORD": "your-password"
}
}
}
}
```
## Documentation
For more information, visit the [Cloud SQL for SQL Server documentation](https://cloud.google.com/sql/docs/sqlserver).