Update docs formatting and bullet point indentation. Update option to move binary into executables folder.
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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:
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Download the Toolbox binary: Download the latest binary for your operating system and architecture from the storage bucket. Check the releases page for OS and CPU architecture support:
https://storage.googleapis.com/genai-toolbox/v0.21.0/<os>/<arch>/toolbox- Replace
<os>withlinux,darwin(macOS), orwindows. - Replace
<arch>withamd64(Intel) orarm64(Apple Silicon).
curl -L -o toolbox https://storage.googleapis.com/genai-toolbox/v0.21.0/linux/amd64/toolbox - Replace
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Make it executable:
chmod +x toolbox -
Move binary to
/usr/local/bin/or/usr/bin/: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, useecho $PATH(orecho %PATH%on Windows).Note: You may need to restart Antigravity for changes to take effect.
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A Google Cloud project with the Cloud SQL Admin API enabled.
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Ensure Application Default Credentials are available in your environment.
-
IAM Permissions:
- Cloud SQL Client (
roles/cloudsql.client)
- Cloud SQL Client (
Configuration
The MCP server is configured using environment variables.
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):
{
"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.