Use the Cloud Healthcare API with MCP and other agents

This guide shows you how to use the MCP Toolbox for Databases to connect the Cloud Healthcare API to a variety of Integrated Development Environments (IDEs) and developer tools. It uses the Model Context Protocol (MCP), an open protocol for connecting large language models (LLMs) to data sources like healthcare datasets, allowing you to search and interact with healthcare data directly from your existing tools.

This guide demonstrates the connection process for the following IDEs:

Cursor
Windsurf (formerly Codeium)
Visual Studio Code (Copilot)
Cline (VS Code extension)
Claude desktop
Claude code

Before you begin

In the Google Cloud console, on the project selector page, select or create a Google Cloud project.
Make sure that billing is enabled for your Google Cloud project.
Enable the Cloud Healthcare API in the Google Cloud project.
Configure the required roles and permissions to complete this task. You will need the Healthcare FHIR Resource Reader role (roles/healthcare.fhirResourceReader) and the Healthcare DICOM Viewer role (roles/healthcare.dicomViewer), or equivalent IAM permissions to connect to the project.
Configure Application Default Credentials (ADC) for your environment.

Install the MCP Toolbox

The toolbox acts as an open-source Model Context Protocol (MCP) server that sits between your IDE and the Cloud Healthcare API, providing a secure and efficient control plane for your AI tools.

Download the latest version of the MCP Toolbox as a binary. Select the binary corresponding to your operating system (OS) and CPU architecture. You must use MCP Toolbox version v0.19.1 or later:
linux/amd64
curl -O https://storage.googleapis.com/genai-toolbox/VERSION/linux/amd64/toolbox
Replace VERSION with the MCP Toolbox version—for example v0.19.1.
macOS darwin/arm64
curl -O https://storage.googleapis.com/genai-toolbox/VERSION/darwin/arm64/toolbox
Replace VERSION with the MCP Toolbox version—for example v0.19.1.
macOS darwin/amd64
curl -O https://storage.googleapis.com/genai-toolbox/VERSION/darwin/amd64/toolbox
Replace VERSION with the MCP Toolbox version—for example v0.19.1.
windows/amd64
curl -O https://storage.googleapis.com/genai-toolbox/VERSION/windows/amd64/toolbox
Replace VERSION with the MCP Toolbox version—for example v0.19.1.
Make the binary executable:
```
chmod +x toolbox
```
Verify the installation:
```
./toolbox --version
```

Set up clients and connections

This section explains how to connect the Cloud Healthcare API to your tools.

Claude code

Install Claude Code.
Create a .mcp.json file in your project root, if it doesn't exist.

Add the configuration, replace the environment variables with your values, and save:

        {
          "mcpServers": {
            "healthcare": {
              "command": "./PATH/TO/toolbox",
              "args": ["--prebuilt","cloud-healthcare","--stdio"],
              "env": {
                "HEALTHCARE_PROJECT": "PROJECT_ID",
                "HEALTHCARE_REGION": "REGION",
                "HEALTHCARE_DATASET": "DATASET_ID"
              }
            }
          }
        }

Restart Claude Code to load the new settings. When it reopens, the tool provides an indication that the configured MCP server has been detected.

Claude desktop

Open Claude Desktop and navigate to Settings.
In the Developer tab, click Edit Config to open the configuration file.

Add the configuration, replace the environment variables with your values, and save:

        {
          "mcpServers": {
            "healthcare": {
              "command": "./PATH/TO/toolbox",
              "args": ["--prebuilt","cloud-healthcare","--stdio"],
              "env": {
                "HEALTHCARE_PROJECT": "PROJECT_ID",
                "HEALTHCARE_REGION": "REGION",
                "HEALTHCARE_DATASET": "DATASET_ID"
              }
            }
          }
        }

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

Cline

Open the Cline extension in VS Code and tap the MCP Servers icon.
Tap Configure MCP Servers to open the configuration file.

Add the following configuration, replace the environment variables with your values, and save:

        {
          "mcpServers": {
            "healthcare": {
              "command": "./PATH/TO/toolbox",
              "args": ["--prebuilt","cloud-healthcare","--stdio"],
              "env": {
                "HEALTHCARE_PROJECT": "PROJECT_ID",
                "HEALTHCARE_REGION": "REGION",
                "HEALTHCARE_DATASET": "DATASET_ID"
              }
            }
          }
        }

A green active status appears after the server connects successfully.

Cursor

Create the .cursor directory in your project root if it doesn't exist.
Create the .cursor/mcp.json file if it doesn't exist and open it.

Add the following configuration, replace the environment variables with your values, and save:

        {
          "mcpServers": {
            "healthcare": {
              "command": "./PATH/TO/toolbox",
              "args": ["--prebuilt","cloud-healthcare","--stdio"],
              "env": {
                "HEALTHCARE_PROJECT": "PROJECT_ID",
                "HEALTHCARE_REGION": "REGION",
                "HEALTHCARE_DATASET": "DATASET_ID"
              }
            }
          }
        }

Open Cursor and navigate to Settings > Cursor Settings > MCP. A green active status appears when the server connects.

Visual Studio Code (Copilot)

Open VS Code and create a .vscode directory in your project root if it does not exist.
Create the .vscode/mcp.json file if it doesn't exist, and open it.

Add the following configuration, replace the environment variables with your values, and save:

        {
          "servers": {
            "healthcare": {
              "command": "./PATH/TO/toolbox",
              "args": ["--prebuilt","cloud-healthcare","--stdio"],
              "env": {
                "HEALTHCARE_PROJECT": "PROJECT_ID",
                "HEALTHCARE_REGION": "REGION",
                "HEALTHCARE_DATASET": "DATASET_ID"
              }
            }
          }
        }

Reload the VS Code window. The MCP-compatible extension automatically detects the configuration and starts the server.

Windsurf

Open Windsurf and navigate to the Cascade assistant.
Click the MCP icon, then click Configure to open the configuration file.

Add the following configuration, replace the environment variables with your values, and save:

        {
          "mcpServers": {
            "healthcare": {
              "command": "./PATH/TO/toolbox",
              "args": ["--prebuilt","cloud-healthcare","--stdio"],
              "env": {
                "HEALTHCARE_PROJECT": "PROJECT_ID",
                "HEALTHCARE_REGION": "REGION",
                "HEALTHCARE_DATASET": "DATASET_ID"
              }
            }

          }
        }

Note: The HEALTHCARE_PROJECT environment variable specifies the default Google Cloud Project ID for the MCP Toolbox to use. All operations, such as searching for patients or looking up DICOM instances, are run within this project.

Use the tools

Your AI tool is now connected to the Cloud Healthcare API using MCP. Try asking your AI assistant to search for FHIR patients, retrieve records for a given patient, look up a DICOM study, or list the DICOM stores in the dataset.

The following tools are available to the LLM:

get_dataset: Retrieves a dataset's details.
list_datasets: Lists health datasets in a project.
list_fhir_stores: Lists the FHIR stores in the given dataset.
list_dicom_stores: Lists the DICOM stores in the given dataset.
get_fhir_store: Gets the configuration of the specified FHIR store.
get_fhir_store_metrics: Gets metrics associated with the FHIR store.
get_fhir_resource: Gets the contents of a FHIR resource.
get_fhir_resource_version: Gets the contents of a version (current or historical) of a FHIR resource.
fhir_patient_everything: Retrieves a FHIR Patient resource and resources related to that patient.
fhir_patient_search: Searches for FHIR patient resources in the FHIR store according to criteria specified.
get_dicom_store: Gets the configuration of the specified DICOM store.
get_dicom_store_metrics: Gets metrics associated with the DICOM store.
search_dicom_studies: Returns a list of matching DICOM studies.
search_dicom_series: Returns a list of matching DICOM series.
search_dicom_instances: Returns a list of matching DICOM instances.
retrieve_dicom_instance_rendered: Returns a base64-encoding of a rendered image in JPEG format for a DICOM instance associated with the given study, series, and SOP Instance UID.

Use the Cloud Healthcare API with MCP and other agents Stay organized with collections Save and categorize content based on your preferences.

Before you begin

Install the MCP Toolbox

linux/amd64

macOS darwin/arm64

macOS darwin/amd64

windows/amd64

Set up clients and connections

Claude code

Claude desktop

Cline

Cursor

Visual Studio Code (Copilot)

Windsurf

Use the tools

Use the Cloud Healthcare API with MCP and other agents