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Update docs formatting and bullet point indentation. Update option to move binary into executables folder.
94 lines
3.9 KiB
Markdown
94 lines
3.9 KiB
Markdown
# Cloud SQL for SQL Server Admin MCP Server
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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.
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## Features
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An editor configured to use the Cloud SQL for SQL Server MCP server can use its AI capabilities to help you:
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- **Provision & Manage Infrastructure** - Create and manage Cloud SQL instances and users
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## Installation and Setup
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### Prerequisites
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* Download and install [MCP Toolbox](https://github.com/googleapis/genai-toolbox):
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1. **Download the Toolbox binary**:
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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:
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`https://storage.googleapis.com/genai-toolbox/v0.21.0/<os>/<arch>/toolbox`
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* Replace `<os>` with `linux`, `darwin` (macOS), or `windows`.
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* Replace `<arch>` with `amd64` (Intel) or `arm64` (Apple Silicon).
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<!-- {x-release-please-start-version} -->
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```
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curl -L -o toolbox https://storage.googleapis.com/genai-toolbox/v0.21.0/linux/amd64/toolbox
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```
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<!-- {x-release-please-end} -->
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2. **Make it executable**:
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```bash
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chmod +x toolbox
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```
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3. **Move binary to `/usr/local/bin/` or `/usr/bin/`**:
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```bash
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sudo mv toolbox /usr/local/bin/
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# sudo mv toolbox /usr/bin/
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```
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**On Windows, move binary to the `WindowsApps\` folder**:
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```
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move "C:\Users\<path-to-binary>\toolbox.exe" "C:\Users\<username>\AppData\Local\Microsoft\WindowsApps\"
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```
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**Tip:** Ensure the destination folder for your binary is included in
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your system's PATH environment variable. To check `PATH`, use `echo
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$PATH` (or `echo %PATH%` on Windows).
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**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](https://cloud.google.com/docs/authentication/gcloud) are available in your environment.
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* IAM Permissions:
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* Cloud SQL Viewer (`roles/cloudsql.viewer`)
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* Cloud SQL Admin (`roles/cloudsql.admin`)
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### Configuration
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Add the following configuration to your MCP client (e.g., `settings.json` for Gemini CLI):
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```json
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{
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"mcpServers": {
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"cloud-sql-sqlserver-admin": {
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"command": "toolbox",
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"args": ["--prebuilt", "cloud-sql-mssql-admin", "--stdio"],
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}
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}
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}
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```
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## Usage
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Once configured, the MCP server will automatically provide Cloud SQL for SQL Server capabilities to your AI assistant. You can:
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* "Create a new Cloud SQL for SQL Server instance named 'e-commerce-prod' in the 'my-gcp-project' project."
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* "Create a new user named 'analyst' with read access to all tables."
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## Server Capabilities
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The Cloud SQL for SQL Server MCP server provides the following tools:
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| Tool Name | Description |
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|:---------------------|:-------------------------------------------------------|
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| `create_instance` | Create an instance (PRIMARY, READ-POOL, or SECONDARY). |
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| `create_user` | Create BUILT-IN or IAM-based users for an instance. |
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| `get_instance` | Get details about an instance. |
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| `get_user` | Get details about a user in an instance. |
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| `list_instances` | List instances in a given project and location. |
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| `list_users` | List users in a given project and location. |
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| `wait_for_operation` | Poll the operations API until the operation is done. |
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## Documentation
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For more information, visit the [Cloud SQL for SQL Server documentation](https://cloud.google.com/sql/docs/sqlserver).
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