MCP Toolbox for Databases

If you are working with Databases, then I suggest that you look at Google project MCP Toolbox for Databases. It is an open source MCP server for databases and supports a wide variety of databases, as shown below from their official documentation:

The MCP Toolbox for Databases provides executables depending on your operating system/architecture and you need to configure and run it locally. The database could be local or even remote (for e.g. a Cloud SQL instance running in Google Cloud).

Let's first download the MCP Toolbox for Databases. Before we download create a folder on your machine that will host the MCP Toolbox binary.

mkdir mcp-toolbox
cd mcp-toolbox

Check out the releases page for your Operation System and Architecture and download the correct binary. I am using a Mac machine with the ARM chip, so here is the script that I am using for the latest version of Toolbox:

export VERSION=0.14.0
curl -O https://storage.googleapis.com/genai-toolbox/v$VERSION/darwin/arm64/toolbox
chmod +x toolbox

Just keep the entire path to the toolbox ready, since we will need that when we configure this MCP Server in the Gemini CLI settings.json file. On my machine, I setup the toolbox in the /Users/romin/mcp-toolbox folder. So the entire path to the Toolbox binary is:

/Users/romin/mcp-toolbox/toolbox

You can refer to the official documentation on how to configure the various databases / data sources that you would the Toolbox to connect to. But one of the quickest ways to get started is via the --preview option for some of the databases that are supported. For e.g. the --preview mode is supported for Google Cloud BigQuery database, so let's try that out for my Google Cloud Project.

The MCP server entry that needs to go into the settings.json file in Gemini CLI is shown below:

"BigQueryServer": {
  "command": "/Users/romin/mcp-toolbox/toolbox",
  "args": ["--prebuilt", "bigquery", "--stdio"],
  "env": {
    "BIGQUERY_PROJECT": "YOUR_GOOGLE_CLOUD_PROJECT_ID"
  }
}

Notice that the command parameter has the full path to the toolbox binary. When we start up Gemini CLI, we can see that additional MCP tools are available now:

Let's query to see what datasets are available in my project. A sample run is shown below:

If you want to customize the tools i.e. the queries and the different options that are allowed, you will need to create a file named tools.yaml , in which all the data source configuration, toolsets, tools and queries will be configured. You will need to provide as a command line parameter while starting up the toolbox binary via the MCP Server option. Let's configure one of the datasource to understand that better.

Here is a configuration for the tools.yaml file for connecting to a public BigQuery dataset in my Google Cloud Project.

sources:
  my-bq-source:
    kind: bigquery
    project: YOUR_PROJECT_ID
tools:
  search_release_notes_bq:
    kind: bigquery-sql
    source: my-bq-source
    statement: |
      SELECT
        product_name,description,published_at
      FROM
        `bigquery-public-data`.`google_cloud_release_notes`.`release_notes`
      WHERE
        DATE(published_at) >= DATE_SUB(CURRENT_DATE(), INTERVAL 7 DAY)
      GROUP BY product_name,description,published_at
      ORDER BY published_at DESC
    description: |
      Use this tool to get information on Google Cloud Release Notes.
toolsets:
  my_bq_toolset:
    - search_release_notes_bq

To configure this toolset/tool in Gemini CLI, we need to provide the command to configure and start the MCP Toolbox for Databases executable and provide the tools.yaml as shown above:

"BigQueryServer": {
  "command": "/Users/romin/mcp-toolbox/toolbox",
  "args": ["--tools-file", "/Users/romin/mcp-toolbox/tools.yaml", "--stdio"],
  "env": {
    "BIGQUERY_PROJECT": "YOUR_GOOGLE_CLOUD_PROJECT_ID"
  }
}

Do check out the configuration documentation page for MCP Toolbox for Databases for more information.