How to Connect to Live HubDB Data from Google ADK Agents (via CData Connect AI)

Jerod Johnson
Director, Technology Evangelism

Leverage the CData Connect AI Remote MCP Server to enable Google ADK agents to securely read and take actions on your HubDB data for you.

Google ADK (Agent Development Kit) is a powerful, model-agnostic framework for building AI agents that can interact with various data sources and services. When combined with CData Connect AI Remote MCP, you can leverage Google ADK to build intelligent agents that interact with your HubDB data in real-time through natural language queries. This article outlines the process of connecting to HubDB using Connect AI Remote MCP and configuring a Google ADK agent to interact with your HubDB data through ADK Web.

CData Connect AI offers a dedicated cloud-to-cloud interface for connecting to HubDB data. The CData Connect AI Remote MCP Server enables secure communication between Google ADK agents and HubDB. This allows your agents to read from and take actions on your HubDB data, all without the need for data replication to a natively supported database. With its inherent optimized data processing capabilities, CData Connect AI efficiently channels all supported SQL operations, including filters and JOINs, directly to HubDB. This leverages server-side processing to swiftly deliver the requested HubDB data.

In this article, we show how to configure a Google ADK agent to conversationally explore (or Vibe Query) your data using natural language. With Connect AI you can build agents with access to live HubDB data, plus hundreds of other sources.

Step 1: Configure HubDB Connectivity for Google ADK

Connectivity to HubDB from Google ADK agents is made possible through CData Connect AI Remote MCP. To interact with HubDB data from your ADK agent, we start by creating and configuring a HubDB connection in CData Connect AI.

Log into Connect AI, click Sources, and then click Add Connection

Select "HubDB" from the Add Connection panel

Enter the necessary authentication properties to connect to HubDB.
There are two authentication methods available for connecting to HubDB data source: OAuth Authentication with a public HubSpot application and authentication with a Private application token.

Using a Custom OAuth App

AuthScheme must be set to "OAuth" in all OAuth flows. Be sure to review the Help documentation for the required connection properties for you specific authentication needs (desktop applications, web applications, and headless machines).

Follow the steps below to register an application and obtain the OAuth client credentials:
1. Log into your HubSpot app developer account.
  - Note that it must be an app developer account. Standard HubSpot accounts cannot create public apps.
2. On the developer account home page, click the Apps tab.
3. Click Create app.
4. On the App info tab, enter and optionally modify values that are displayed to users when they connect. These values include the public application name, application logo, and a description of the application.
5. On the Auth tab, supply a callback URL in the "Redirect URLs" box.
  - If you're creating a desktop application, set this to a locally accessible URL like http://localhost:33333.
  - If you are creating a Web application, set this to a trusted URL where you want users to be redirected to when they authorize your application.
6. Click Create App. HubSpot then generates the application, along with its associated credentials.
7. On the Auth tab, note the Client ID and Client secret. You will use these later to configure the driver.
8. Under Scopes, select any scopes you need for your application's intended functionality.
  
  A minimum of the following scopes is required to access tables:
  - hubdb
  - oauth
  - crm.objects.owners.read
9. Click Save changes.
10. Install the application into a production portal with access to the features that are required by the integration.
  - Under "Install URL (OAuth)", click Copy full URL to copy the installation URL for your application.
  - Navigate to the copied link in your browser. Select a standard account in which to install the application.
  - Click Connect app. You can close the resulting tab.
Using a Private App

To connect using a HubSpot private application token, set the AuthScheme property to "PrivateApp."

You can generate a private application token by following the steps below:
1. In your HubDB account, click the settings icon (the gear) in the main navigation bar.
2. In the left sidebar menu, navigate to Integrations > Private Apps.
3. Click Create private app.
4. On the Basic Info tab, configure the details of your application (name, logo, and description).
5. On the Scopes tab, select Read or Write for each scope you want your private application to be able to access.
6. A minimum of hubdb and crm.objects.owners.read is required to access tables.
7. After you are done configuring your application, click Create app in the top right.
8. Review the info about your application's access token, click Continue creating, and then Show token.
9. Click Copy to copy the private application token.
To connect, set PrivateAppToken to the private application token you retrieved.
Click Save & Test
Navigate to the Permissions tab in the Add HubDB Connection page and update the User-based permissions.

Add a Personal Access Token

A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from your Google ADK agent. It is best practice to create a separate PAT for each service to maintain granularity of access.

Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
On the Settings page, go to the Access Tokens section and click Create PAT.
Give the PAT a name and click Create.
The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, we are ready to connect to HubDB data from your Google ADK agent.

Step 2: Configure Your Google ADK Agent for CData Connect AI

Follow these steps to configure your Google ADK agent to connect to CData Connect AI. You can use our pre-built agent as a starting point, available at https://github.com/CDataSoftware/adk-mcp-client, or follow the instructions below to create your own.

Ensure you have the Google ADK Python SDK installed. If not, install it using pip:
```
pip install google-genkit google-adk
```
Create or update your agent's configuration file (typically agent.py) to include the CData Connect AI MCP connection. You'll need to configure the MCP toolset with your Connect AI credentials.
Set up your environment variables or configuration for the MCP server connection. Create a .env file in your project root with the following variables:
```
MCP_SERVER_URL=https://mcp.cloud.cdata.com/mcp
MCP_USERNAME=YOUR_EMAIL
MCP_PASSWORD=YOUR_PAT
    
```
Replace YOUR_EMAIL with your Connect AI email address and YOUR_PAT with the Personal Access Token created in Step 1.

Configure your agent.py file to use the CData Connect AI MCP Server. Here's an example configuration:

import os
import base64
from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import MCPToolset
from google.adk.tools.mcp_tool.mcp_session_manager import StreamableHTTPConnectionParams
from dotenv import load_dotenv

# Load environment variables
load_dotenv()

# Get configuration from environment
MCP_SERVER_URL = os.getenv('MCP_SERVER_URL', 'https://mcp.cloud.cdata.com/mcp')
MCP_USERNAME = os.getenv('MCP_USERNAME', '')
MCP_PASSWORD = os.getenv('MCP_PASSWORD', '')

# Create auth header for MCP server
auth_header = {}
if MCP_USERNAME and MCP_PASSWORD:
    credentials = f"{MCP_USERNAME}:{MCP_PASSWORD}"
    auth_header = {"Authorization": f"Basic {base64.b64encode(credentials.encode()).decode()}"}

# Define your agent with CData MCP tools
root_agent = LlmAgent(
    model='gemini-2.0-flash-exp',  # You can use any supported model
    name='data_query_assistant',
    instruction="""You are a data query assistant with access to HubDB data through CData Connect AI.
    
    You can help users explore and query their HubDB data in real-time.
    Use the available MCP tools to:
    - List available databases and schemas
    - Explore table structures
    - Execute SQL queries
    - Provide insights about the data
    
    Always explain what you're doing and format results clearly.""",
    
    tools=[
        MCPToolset(
            connection_params=StreamableHTTPConnectionParams(
                url=MCP_SERVER_URL,
                headers=auth_header
            )
        )
    ],
)

Run your agent with ADK Web. From your project directory, execute:
```
adk web --port 5000 .
```
Note: If you installed ADK with pip install --user, the adk command may not be in your PATH. You can either:
- Use the full path: ~/Library/Python/3.x/bin/adk (on macOS)
- Add to PATH: export PATH="$HOME/Library/Python/3.x/bin:$PATH"
- Use a virtual environment where the PATH is automatically configured
Open the ADK Web interface in your browser (typically http://localhost:5000).
Select your agent from the dropdown menu (it will be named based on the name parameter in your agent configuration).
Start interacting with your HubDB data through natural language queries. Your agent now has access to your HubDB data through the CData Connect AI MCP Server.

Step 3: Build Intelligent Agents with Live HubDB Data Access

With your Google ADK agent configured and connected to CData Connect AI, you can now build sophisticated agents that interact with your HubDB data using natural language. The MCP integration provides your agents with powerful data access capabilities.

Available MCP Tools for Your Agent

Your Google ADK agent has access to the following CData Connect AI MCP tools:

queryData: Execute SQL queries against connected data sources and retrieve results
getCatalogs: Retrieve a list of available connections from CData Connect AI
getSchemas: Retrieve database schemas for a specific catalog
getTables: Retrieve database tables for a specific catalog and schema
getColumns: Retrieve column metadata for a specific table
getProcedures: Retrieve stored procedures for a specific catalog and schema
getProcedureParameters: Retrieve parameter metadata for stored procedures
executeProcedure: Execute stored procedures with parameters

Example Use Cases

Here are some examples of what your Google ADK agents can do with live HubDB data access:

Data Analysis Agent: Build an agent that analyzes trends, patterns, and anomalies in your HubDB data
Report Generation Agent: Create agents that generate custom reports based on natural language requests
Data Quality Agent: Develop agents that monitor and validate data quality in real-time
Business Intelligence Agent: Build agents that answer complex business questions by querying multiple data sources
Automated Workflow Agent: Create agents that trigger actions based on data conditions in HubDB

Testing Your Agent

Once deployed to ADK Web, you can interact with your agent through natural language queries. For example:

"Show me all customers from the last 30 days"
"What are the top performing products this quarter?"
"Analyze sales trends and identify anomalies"
"Generate a summary report of active projects"
"Find all records that match specific criteria"

Your Google ADK agent will automatically translate these natural language queries into appropriate SQL queries and execute them against your HubDB data through the CData Connect AI MCP Server, providing real-time insights without requiring users to write complex SQL or understand the underlying data structure.

Get CData Connect AI

To get live data access to 300+ SaaS, Big Data, and NoSQL sources directly from your Google ADK agents and cloud applications, try CData Connect AI today!

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