Connect your IDE to Cloud SQL

MySQL  |  PostgreSQL  |  SQL Server

This guide shows you how to use theMCP Toolbox forDatabases to connect yourCloud SQL instance to various Integrated Development Environments (IDEs)and developer tools that supportModel Context Protocol(MCP). Use these tools to runSQL queries and interact with your database.

The Model Context Protocol (MCP) is an open protocol for connecting largelanguage models (LLMs) to data sources such as Cloud SQL. The IDEssupported are:

Before you begin

  1. In the Google Cloud console, on theproject selectorpage,select or create a Google Cloud project.

  2. Make sure that billing is enabled for your Google Cloudproject.

  3. Enable the Cloud SQL Admin API in the Google Cloudproject.

  4. VerifyPublic IP is set up forCloud SQL instance. By default, Cloud SQL assigns a public IPaddress to a new instance. Toolbox connects securely using theCloud SQL Language Connectors.

  5. Configure the required roles and permissions to complete this task. You needCloud SQL >Clientrole (roles/cloudsql.client) or equivalent Identity and Access Management permissions toconnect to the instance.

  6. ConfigureApplication Default Credentials(ADC) for yourenvironment.

  7. Create or reusea database user,and have the username and password ready.

Install the MCP Toolbox

  1. To install the toolbox, download the binary that corresponds to youroperating system and CPU architecture.

    linux/amd64

    curl -O https://storage.googleapis.com/genai-toolbox/v0.7.0/linux/amd64/toolbox

    darwin/arm64

    curl -O https://storage.googleapis.com/genai-toolbox/v0.7.0/darwin/arm64/toolbox

    darwin/amd64

    curl -O https://storage.googleapis.com/genai-toolbox/v0.7.0/darwin/amd64/toolbox

    windows/amd64

    curl -O https://storage.googleapis.com/genai-toolbox/v0.7.0/windows/amd64/toolbox

  2. Make the binary executable:

    chmod+xtoolbox

  3. Verify the installation using the following command:

    ./toolbox--version

Configure the MCP Client

Claude code


1. InstallClaude Code.
2. Create.mcp.json file in your project root if it does not exist.
3. Add configuration, replace the environment variables with your values, and save:

{  "mcpServers": {    "cloud-sql-postgres": {      "command": "./PATH/TO/toolbox",      "args": ["--prebuilt","cloud-sql-postgres","--stdio"],      "env": {        "CLOUD_SQL_POSTGRES_PROJECT": "PROJECT_ID",        "CLOUD_SQL_POSTGRES_REGION": "REGION",        "CLOUD_SQL_POSTGRES_INSTANCE": "INSTANCE_ID",        "CLOUD_SQL_POSTGRES_DATABASE": "DATABASE_NAME",        "CLOUD_SQL_POSTGRES_USER": "USER_ID",        "CLOUD_SQL_POSTGRES_PASSWORD": "PASSWORD"      }    }  }}

Claude desktop


1. OpenClaude Desktop and navigate to Settings.
2. Under the Developer tab, tap Edit Config to open the configuration file.
3. Add configuration, replace the environment variables with your values, and save:

{  "mcpServers": {    "cloud-sql-postgres": {      "command": "./PATH/TO/toolbox",      "args": ["--prebuilt","cloud-sql-postgres","--stdio"],      "env": {        "CLOUD_SQL_POSTGRES_PROJECT": "PROJECT_ID",        "CLOUD_SQL_POSTGRES_REGION": "REGION",        "CLOUD_SQL_POSTGRES_INSTANCE": "INSTANCE_ID",        "CLOUD_SQL_POSTGRES_DATABASE": "DATABASE_NAME",        "CLOUD_SQL_POSTGRES_USER": "USER_ID",        "CLOUD_SQL_POSTGRES_PASSWORD": "PASSWORD"    }  }}

5. Restart Claude Desktop.
6. The new chat screen displays a hammer (MCP) icon with the new MCP server available.

Cline


1. OpenCline extension in VS Code and tapMCP Servers icon.
2. Tap Configure MCP Servers to open the configuration file.
3. Add the following configuration, replace the environment variables with your values, and save:

{  "mcpServers": {    "cloud-sql-postgres": {      "command": "./PATH/TO/toolbox",      "args": ["--prebuilt","cloud-sql-postgres","--stdio"],      "env": {        "CLOUD_SQL_POSTGRES_PROJECT": "PROJECT_ID",        "CLOUD_SQL_POSTGRES_REGION": "REGION",        "CLOUD_SQL_POSTGRES_INSTANCE": "INSTANCE_ID",        "CLOUD_SQL_POSTGRES_DATABASE": "DATABASE_NAME",        "CLOUD_SQL_POSTGRES_USER": "USER_ID",        "CLOUD_SQL_POSTGRES_PASSWORD": "PASSWORD"      }    }  }}

4. A green active status appears after the server connects successfully.

Cursor


1. Create.cursor directory in your project root if it does not exist.
2. Create.cursor/mcp.json file if it does not exist and open it.
3. Add the following configuration, replace the environment variables with your values, and save:

{  "mcpServers": {    "cloud-sql-postgres": {      "command": "./PATH/TO/toolbox",      "args": ["--prebuilt","cloud-sql-postgres","--stdio"],      "env": {        "CLOUD_SQL_POSTGRES_PROJECT": "PROJECT_ID",        "CLOUD_SQL_POSTGRES_REGION": "REGION",        "CLOUD_SQL_POSTGRES_INSTANCE": "INSTANCE_ID",        "CLOUD_SQL_POSTGRES_DATABASE": "DATABASE_NAME",        "CLOUD_SQL_POSTGRES_USER": "USER_ID",        "CLOUD_SQL_POSTGRES_PASSWORD": "PASSWORD"      }    }  }}

4. OpenCursor and navigate toSettings > Cursor Settings > MCP. A green active status appears when the server connects.

Visual Studio Code (Copilot)


1. OpenVS Code and create.vscode directory in your project root if it does not exist.
2. Create.vscode/mcp.json file if it does not exist, and open it.
3. Add the following configuration, replace the environment variables with your values, and save:

{  "mcp": {      "servers": {        "cloud-sql-postgres": {          "command": "./PATH/TO/toolbox",          "args": ["--prebuilt","cloud-sql-postgres","--stdio"],          "env": {            "CLOUD_SQL_POSTGRES_PROJECT": "PROJECT_ID",            "CLOUD_SQL_POSTGRES_REGION": "REGION",            "CLOUD_SQL_POSTGRES_INSTANCE": "INSTANCE_ID",            "CLOUD_SQL_POSTGRES_DATABASE": "DATABASE_NAME",            "CLOUD_SQL_POSTGRES_USER": "USER_ID",            "CLOUD_SQL_POSTGRES_PASSWORD": "PASSWORD"          }        }      }    }}

Windsurf


1. OpenWindsurf and navigate to Cascade assistant.
2. Tap MCP icon, then tapConfigure to open the configuration file.
3. Add the following configuration, replace the environment variables with your values, and save:

{  "mcpServers": {    "cloud-sql-postgres": {      "command": "./PATH/TO/toolbox",      "args": ["--prebuilt","cloud-sql-postgres","--stdio"],      "env": {        "CLOUD_SQL_POSTGRES_PROJECT": "PROJECT_ID",        "CLOUD_SQL_POSTGRES_REGION": "REGION",        "CLOUD_SQL_POSTGRES_INSTANCE": "INSTANCE_ID",        "CLOUD_SQL_POSTGRES_DATABASE": "DATABASE_NAME",        "CLOUD_SQL_POSTGRES_USER": "USER_ID",        "CLOUD_SQL_POSTGRES_PASSWORD": "PASSWORD">      }    }  }}

Gemini CLI


1. Install theGemini CLI.
2. In your working directory, create a folder named.gemini. Within it, create asettings.json file.
3. Add the following configuration, replace the environment variables with your values, and then save:

{  "mcpServers": {    "cloud-sql-postgres": {      "command": "./PATH/TO/toolbox",      "args": ["--prebuilt","cloud-sql-postgres","--stdio"],      "env": {        "CLOUD_SQL_POSTGRES_PROJECT": "PROJECT_ID",        "CLOUD_SQL_POSTGRES_REGION": "REGION",        "CLOUD_SQL_POSTGRES_INSTANCE": "INSTANCE_ID",        "CLOUD_SQL_POSTGRES_DATABASE": "DATABASE_NAME",        "CLOUD_SQL_POSTGRES_USER": "USER_ID",        "CLOUD_SQL_POSTGRES_PASSWORD": "PASSWORD">      }    }  }}

Gemini Code Assist


1. Install theGemini Code Assist extension in Visual Studio Code.
2. Enable Agent Mode in Gemini Code Assist chat.
3. In your working directory, create a folder named.gemini. Within it, create asettings.json file.
4. Add the following configuration, replace the environment variables with your values, and then save:

{  "mcpServers": {    "cloud-sql-postgres": {      "command": "./PATH/TO/toolbox",      "args": ["--prebuilt","cloud-sql-postgres","--stdio"],      "env": {        "CLOUD_SQL_POSTGRES_PROJECT": "PROJECT_ID",        "CLOUD_SQL_POSTGRES_REGION": "REGION",        "CLOUD_SQL_POSTGRES_INSTANCE": "INSTANCE_ID",        "CLOUD_SQL_POSTGRES_DATABASE": "DATABASE_NAME",        "CLOUD_SQL_POSTGRES_USER": "USER_ID",        "CLOUD_SQL_POSTGRES_PASSWORD": "PASSWORD">      }    }  }}

Use Tools

Your AI tool is now connected to Cloud SQL using MCP. Try asking your AIassistant to list tables, create a table, or define and execute other SQLstatements.

The following tools are available to the LLM:

  1. list_tables: lists tables and descriptions
  2. execute_sql: execute any SQL statement
Note: Prebuilt tools are version 1.0 or earlier and may containdifferences between versions.

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Last updated 2025-07-14 UTC.