mirror of
https://github.com/googleapis/genai-toolbox.git
synced 2026-02-11 07:35:05 -05:00
e0245946ea
## 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: - [x] 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>
91 lines
3.8 KiB
Markdown
91 lines
3.8 KiB
Markdown
# Cloud Spanner MCP Server
|
|
|
|
The Cloud Spanner Model Context Protocol (MCP) Server gives AI-powered development tools the ability to work with your Google Cloud Spanner databases. It supports executing SQL queries and exploring schemas.
|
|
|
|
## Features
|
|
|
|
An editor configured to use the Cloud Spanner MCP server can use its AI capabilities to help you:
|
|
|
|
- **Query Data** - Execute DML and DQL SQL queries
|
|
- **Explore Schema** - List tables and view schema details
|
|
|
|
## Prerequisites
|
|
|
|
* [Node.js](https://nodejs.org/) installed.
|
|
* A Google Cloud project with the **Cloud Spanner API** enabled.
|
|
* Ensure [Application Default Credentials](https://cloud.google.com/docs/authentication/gcloud) are available in your environment.
|
|
* IAM Permissions:
|
|
* Cloud Spanner Database User (`roles/spanner.databaseUser`) (for data access)
|
|
* Cloud Spanner Viewer (`roles/spanner.viewer`) (for schema access)
|
|
|
|
## Install & Configuration
|
|
|
|
1. In the Antigravity MCP Store, click the "Install" button.
|
|
> [!NOTE]
|
|
> On first use, the installation process automatically downloads and uses
|
|
> [MCP Toolbox](https://www.npmjs.com/package/@toolbox-sdk/server)
|
|
> `>=0.26.0`. To update MCP Toolbox, use:
|
|
> ```npm i -g @toolbox-sdk/server@latest```
|
|
> To always run the latest version, update the MCP server configuration to use:
|
|
> ```npx -y @toolbox-sdk/server@latest --prebuilt spanner```.
|
|
|
|
2. Add the required inputs for your [instance](https://docs.cloud.google.com/spanner/docs/instances) in the configuration pop-up, then click "Save". You can update this configuration at any time in the "Configure" tab.
|
|
|
|
You'll now be able to see all enabled tools in the "Tools" tab.
|
|
|
|
> [!NOTE]
|
|
> If you encounter issues with Windows Defender blocking the execution, you may need to configure an allowlist. See [Configure exclusions for Microsoft Defender Antivirus](https://learn.microsoft.com/en-us/microsoft-365/security/defender-endpoint/configure-exclusions-microsoft-defender-antivirus?view=o365-worldwide) for more details.
|
|
|
|
## Usage
|
|
|
|
Once configured, the MCP server will automatically provide Cloud Spanner capabilities to your AI assistant. You can:
|
|
|
|
* "Execute a DML query to update customer names."
|
|
* "List all tables in the `my-database`."
|
|
* "Execute a DQL query to select data from `orders` table."
|
|
|
|
## Server Capabilities
|
|
|
|
The Cloud Spanner MCP server provides the following tools:
|
|
|
|
| Tool Name | Description |
|
|
|:------------------|:-----------------------------------------------------------------|
|
|
| `execute_sql` | Use this tool to execute DML SQL. |
|
|
| `execute_sql_dql` | Use this tool to execute DQL SQL. |
|
|
| `list_tables` | Lists detailed schema information for user-created tables. |
|
|
| `list_graphs` | Lists detailed graph schema information for user-created graphs. |
|
|
|
|
## Custom MCP Server Configuration
|
|
|
|
The MCP server is configured using environment variables.
|
|
|
|
```bash
|
|
export SPANNER_PROJECT="<your-gcp-project-id>"
|
|
export SPANNER_INSTANCE="<your-spanner-instance-id>"
|
|
export SPANNER_DATABASE="<your-spanner-database-id>"
|
|
export SPANNER_DIALECT="googlesql" # Optional: "googlesql" or "postgresql". Defaults to "googlesql".
|
|
```
|
|
|
|
Add the following configuration to your MCP client (e.g., `settings.json` for Gemini CLI, `mcp_config.json` for Antigravity):
|
|
|
|
```json
|
|
{
|
|
"mcpServers": {
|
|
"spanner": {
|
|
"command": "npx",
|
|
"args": ["-y", "@toolbox-sdk/server", "--prebuilt", "spanner", "--stdio"],
|
|
"env": {
|
|
"SPANNER_PROJECT": "your-project-id",
|
|
"SPANNER_INSTANCE": "your-instance-id",
|
|
"SPANNER_DATABASE": "your-database-name",
|
|
"SPANNER_DIALECT": "googlesql"
|
|
}
|
|
}
|
|
}
|
|
}
|
|
```
|
|
|
|
## Documentation
|
|
|
|
For more information, visit the [Cloud Spanner documentation](https://cloud.google.com/spanner/docs).
|