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genai-toolbox/docs/CLOUDSQLMSSQL_README.md
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# 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
## 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 Client (`roles/cloudsql.client`)
### 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`.
```
> **Note:** If your instance uses private IPs, you must run the MCP server in the same Virtual Private Cloud (VPC) network.
Add the following configuration to your MCP client (e.g., `settings.json` for Gemini CLI):
```json
{
"mcpServers": {
"cloud-sql-mssql": {
"command": "toolbox",
"args": ["--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"
}
}
}
}
```
## 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. |
## Documentation
For more information, visit the [Cloud SQL for SQL Server documentation](https://cloud.google.com/sql/docs/sqlserver).