# Cloud SQL for SQL Server Admin 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:

- **Provision & Manage Infrastructure** - Create and manage Cloud SQL instances and users

## Installation and Setup

### Prerequisites

*   Download and install [MCP Toolbox](https://github.com/googleapis/genai-toolbox):
    1.  **Download the Toolbox binary**:
        Download the latest binary for your operating system and architecture from the storage bucket. Check the [releases page](https://github.com/googleapis/genai-toolbox/releases) for OS and CPU architecture support:
        `https://storage.googleapis.com/genai-toolbox/v0.21.0/<os>/<arch>/toolbox`
        *   Replace `<os>` with `linux`, `darwin` (macOS), or `windows`.
        *   Replace `<arch>` with `amd64` (Intel) or `arm64` (Apple Silicon).
      
        <!-- {x-release-please-start-version} -->
        ```
        curl -L -o toolbox https://storage.googleapis.com/genai-toolbox/v0.21.0/linux/amd64/toolbox
        ```
        <!-- {x-release-please-end} -->
    2.  **Make it executable**:
        ```bash
        chmod +x toolbox
        ```

    3.  **Move binary to `/usr/local/bin/` or `/usr/bin/`**:
        ```bash
        sudo mv toolbox /usr/local/bin/
        # sudo mv toolbox /usr/bin/
        ```

        **On Windows, move binary to the `WindowsApps\` folder**:
        ```
        move "C:\Users\<path-to-binary>\toolbox.exe" "C:\Users\<username>\AppData\Local\Microsoft\WindowsApps\"
        ```
    
        **Tip:** Ensure the destination folder for your binary is included in
        your system's PATH environment variable. To check `PATH`, use `echo
        $PATH` (or `echo %PATH%` on Windows).

        **Note:** You may need to restart Antigravity for changes to take effect.

*   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 Viewer (`roles/cloudsql.viewer`)
  * Cloud SQL Admin (`roles/cloudsql.admin`)

### Configuration

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

```json
{
  "mcpServers": {
    "cloud-sql-sqlserver-admin": {
      "command": "toolbox",
      "args": ["--prebuilt", "cloud-sql-mssql-admin", "--stdio"],
    }
  }
}
```

## Usage

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

  * "Create a new Cloud SQL for SQL Server instance named 'e-commerce-prod' in the 'my-gcp-project' project."
  * "Create a new user named 'analyst' with read access to all tables."

## Server Capabilities

The Cloud SQL for SQL Server MCP server provides the following tools:

| Tool Name            | Description                                            |
|:---------------------|:-------------------------------------------------------|
| `create_instance`    | Create an instance (PRIMARY, READ-POOL, or SECONDARY). |
| `create_user`        | Create BUILT-IN or IAM-based users for an instance.    |
| `get_instance`       | Get details about an instance.                         |
| `get_user`           | Get details about a user in an instance.               |
| `list_instances`     | List instances in a given project and location.        |
| `list_users`         | List users in a given project and location.            |
| `wait_for_operation` | Poll the operations API until the operation is done.   |

## Documentation

For more information, visit the [Cloud SQL for SQL Server documentation](https://cloud.google.com/sql/docs/sqlserver).