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## Description > Should include a concise description of the changes (bug or feature), it's > impact, along with a summary of the solution ## PR Checklist > Thank you for opening a Pull Request! Before submitting your PR, there are a > few things you can do to make sure it goes smoothly: - [ ] Make sure you reviewed [CONTRIBUTING.md](https://github.com/googleapis/genai-toolbox/blob/main/CONTRIBUTING.md) - [ ] Make sure to open an issue as a [bug/issue](https://github.com/googleapis/genai-toolbox/issues/new/choose) before writing your code! That way we can discuss the change, evaluate designs, and agree on the general idea - [ ] Ensure the tests and linter pass - [ ] Code coverage does not decrease (if any source code was changed) - [ ] Appropriate docs were updated (if necessary) - [ ] Make sure to add `!` if this involve a breaking change 🛠️ Fixes #<issue_number_goes_here> --------- Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
102 lines
3.8 KiB
Markdown
102 lines
3.8 KiB
Markdown
# Cloud SQL for SQL Server 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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- **Query Data** - Execute SQL queries
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- **Explore Schema** - List tables and view schema details
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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. **Add the binary to $PATH in `.~/bash_profile`**:
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```bash
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export PATH=$PATH:/path/to/toolbox
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```
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**Note:** You may need to restart Antigravity for changes to take effect.
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Windows OS users will need to follow one of the Windows-specific methods.
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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 Client (`roles/cloudsql.client`)
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### Configuration
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The MCP server is configured using environment variables.
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```bash
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export CLOUD_SQL_MSSQL_PROJECT="<your-gcp-project-id>"
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export CLOUD_SQL_MSSQL_REGION="<your-cloud-sql-region>"
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export CLOUD_SQL_MSSQL_INSTANCE="<your-cloud-sql-instance-id>"
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export CLOUD_SQL_MSSQL_DATABASE="<your-database-name>"
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export CLOUD_SQL_MSSQL_USER="<your-database-user>" # Optional
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export CLOUD_SQL_MSSQL_PASSWORD="<your-database-password>" # Optional
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export CLOUD_SQL_MSSQL_IP_TYPE="PUBLIC" # Optional: `PUBLIC`, `PRIVATE`, `PSC`. Defaults to `PUBLIC`.
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```
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> **Note:** If your instance uses private IPs, you must run the MCP server in the same Virtual Private Cloud (VPC) network.
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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-mssql": {
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"command": "toolbox",
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"args": ["--prebuilt", "cloud-sql-mssql", "--stdio"],
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"env": {
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"CLOUD_SQL_MSSQL_PROJECT": "your-project-id",
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"CLOUD_SQL_MSSQL_REGION": "your-region",
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"CLOUD_SQL_MSSQL_INSTANCE": "your-instance-id",
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"CLOUD_SQL_MSSQL_DATABASE": "your-database-name",
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"CLOUD_SQL_MSSQL_USER": "your-username",
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"CLOUD_SQL_MSSQL_PASSWORD": "your-password"
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}
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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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* "Select top 10 rows from the customers table."
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* "List all tables in the database."
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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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| `execute_sql` | Use this tool to execute SQL. |
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| `list_tables` | Lists detailed schema information for user-created tables. |
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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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