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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.
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.
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:
There are certain connection properties you need to set before you can connect. You can obtain these as follows:
To connect with IBM Cloud Object Storage, you need an API Key. You can obtain this as follows:
If you have multiple accounts, specify the CloudObjectStorageCRN explicitly. To find the appropriate value, you can:
You can now set the following to connect to data:
When you connect, the connector completes the OAuth process.
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.
With the connection configured and a PAT generated, we are ready to connect to IBM Cloud Object Storage data from your Google ADK agent.
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.
pip install google-genkit google-adk
MCP_SERVER_URL=https://mcp.cloud.cdata.com/mcp MCP_USERNAME=YOUR_EMAIL MCP_PASSWORD=YOUR_PATReplace YOUR_EMAIL with your Connect AI email address and YOUR_PAT with the Personal Access Token created in Step 1.
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
)
)
],
)
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:
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.
Your Google ADK agent has access to the following CData Connect AI MCP tools:
Here are some examples of what your Google ADK agents can do with live IBM Cloud Object Storage data access:
Once deployed to ADK Web, you can interact with your agent through natural language queries. For example:
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.
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!
Learn more about CData Connect AI or sign up for free trial access:
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