How to Connect to Live IBM Cloud Object Storage 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 IBM Cloud Object Storage 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 IBM Cloud Object Storage data in real-time through natural language queries. This article outlines the process of connecting to IBM Cloud Object Storage using Connect AI Remote MCP and configuring a Google ADK agent to interact with your IBM Cloud Object Storage data through ADK Web.

CData Connect AI offers a dedicated cloud-to-cloud interface for connecting to IBM Cloud Object Storage data. The CData Connect AI Remote MCP Server enables secure communication between Google ADK agents and IBM Cloud Object Storage. This allows your agents to read from and take actions on your IBM Cloud Object Storage 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 IBM Cloud Object Storage. This leverages server-side processing to swiftly deliver the requested IBM Cloud Object Storage 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 IBM Cloud Object Storage data, plus hundreds of other sources.

Step 1: Configure IBM Cloud Object Storage Connectivity for Google ADK

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

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

Select "IBM Cloud Object Storage" from the Add Connection panel

Enter the necessary authentication properties to connect to IBM Cloud Object Storage.
Register a New Instance of Cloud Object Storage

If you do not already have Cloud Object Storage in your IBM Cloud account, follow the procedure below to install an instance of SQL Query in your account:
1. Log in to your IBM Cloud account.
2. Navigate to the page, choose a name for your instance and click Create. You will be redirected to the instance of Cloud Object Storage you just created.
Connecting using OAuth Authentication

There are certain connection properties you need to set before you can connect. You can obtain these as follows:

API Key

To connect with IBM Cloud Object Storage, you need an API Key. You can obtain this as follows:
1. Log in to your IBM Cloud account.
2. Navigate to the Platform API Keys page.
3. On the middle-right corner click "Create an IBM Cloud API Key" to create a new API Key.
4. In the pop-up window, specify the API Key name and click "Create". Note the API Key as you can never access it again from the dashboard.
Cloud Object Storage CRN

If you have multiple accounts, specify the CloudObjectStorageCRN explicitly. To find the appropriate value, you can:
- Query the Services view. This will list your IBM Cloud Object Storage instances along with the CRN for each.
- Locate the CRN directly in IBM Cloud. To do so, navigate to your IBM Cloud Dashboard. In the Resource List, Under Storage, select your Cloud Object Storage resource to get its CRN.
Connecting to Data

You can now set the following to connect to data:
- InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to avoid repeating the OAuth exchange and manually setting the OAuthAccessToken.
- ApiKey: Set this to your API key which was noted during setup.
- CloudObjectStorageCRN (Optional): Set this to the cloud object storage CRN you want to work with. While the connector attempts to retrieve this automatically, specifying this explicitly is recommended if you have more than Cloud Object Storage account.
When you connect, the connector completes the OAuth process.
1. Extracts the access token and authenticates requests.
2. Saves OAuth values in OAuthSettingsLocation to be persisted across connections.
Click Save & Test
Navigate to the Permissions tab in the Add IBM Cloud Object Storage 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 IBM Cloud Object Storage 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 IBM Cloud Object Storage data through CData Connect AI.
    
    You can help users explore and query their IBM Cloud Object Storage 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 IBM Cloud Object Storage data through natural language queries. Your agent now has access to your IBM Cloud Object Storage data through the CData Connect AI MCP Server.

Step 3: Build Intelligent Agents with Live IBM Cloud Object Storage Data Access

With your Google ADK agent configured and connected to CData Connect AI, you can now build sophisticated agents that interact with your IBM Cloud Object Storage 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 IBM Cloud Object Storage data access:

Data Analysis Agent: Build an agent that analyzes trends, patterns, and anomalies in your IBM Cloud Object Storage 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 IBM Cloud Object Storage

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 IBM Cloud Object Storage 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 hundreds of SaaS, Big Data, and NoSQL sources directly from your Google ADK agents and cloud applications, try CData Connect AI today!

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How to Connect to Live IBM Cloud Object Storage Data from Google ADK Agents (via CData Connect AI)

Step 1: Configure IBM Cloud Object Storage Connectivity for Google ADK

Register a New Instance of Cloud Object Storage

Connecting using OAuth Authentication

API Key

Cloud Object Storage CRN

Connecting to Data