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Grok AI is a large language model developed by xAI for real-time reasoning, tool invocation, and agentic workflows. It enables developers to build AI agents that can reason over live data, discover tools dynamically, and take intelligent actions.
CData Connect AI provides a secure cloud-to-cloud interface for integrating hundreds of enterprise data sources with Grok AI. Using Connect AI, live AlloyDB data is exposed through a remote MCP endpoint without replication, allowing Grok AI agents to securely query and analyze governed enterprise data in real time.
To enable Grok to query live AlloyDB data, first create a AlloyDB connection in CData Connect AI. This connection is exposed through the CData Remote MCP Server.
The following connection properties are usually required in order to connect to AlloyDB.
You can also optionally set the following:
Standard authentication (using the user/password combination supplied earlier) is the default form of authentication.
No further action is required to leverage Standard Authentication to connect.
There are additional methods of authentication available which must be enabled in the pg_hba.conf file on the AlloyDB server.
Find instructions about authentication setup on the AlloyDB Server here.
This authentication method must be enabled by setting the auth-method in the pg_hba.conf file to md5.
This authentication method must be enabled by setting the auth-method in the pg_hba.conf file to scram-sha-256.
The authentication with Kerberos is initiated by AlloyDB Server when the β is trying to connect to it. You should set up Kerberos on the AlloyDB Server to activate this authentication method. Once you have Kerberos authentication set up on the AlloyDB Server, see the Kerberos section of the help documentation for details on how to authenticate with Kerberos.
π Configuring connection properties
Click Create & Test.
A Personal Access Token (PAT) authenticates MCP requests from Agno to CData Connect AI.
Remote MCP Tools allow Grok to connect to external MCP (Model Context Protocol) servers, extending its capabilities with custom tools from third parties or your own implementations. Simply specify a server URL and optional configuration xAI manages the MCP server connection and interaction on your behalf.
Open the terminal and install the required dependencies for the MCP integration using pip.
pip install xai-sdk==1.4.0
The xai-sdk (v1.4.0) enables Remote MCP tools, and python-dotenv is used to securely load environment variables.
pip install python-dotenv
After generating an API key, user need to save it somewhere safe. Recommended option is to export it as an environment variable in your terminal or save it to a .env file.
Initialize the Grok client and configure the MCP connection to CData Connect AI. The code below establishes a secure connection and sends a natural language query to your data source.
import os
from xai_sdk import Client
from xai_sdk.chat import user
from xai_sdk.tools import mcp
client = Client(api_key="Your_xAI-API_KEY")
chat = client.chat.create(
model="grok-4-1-fast-non-reasoning",
tools=[
mcp(
server_url="https://mcp.cloud.cdata.com/mcp",
extra_headers={"Authorization": "Basic Username:PAT"} #Base64 Encoded Username:PAT
)
],
include=["verbose_streaming"],
)
chat.append(user("List the top two catalogs for me please"))
is_thinking = True
for response, chunk in chat.stream():
# View the server-side tool calls as they are being made in real-time
for tool_call in chunk.tool_calls:
print(f"
Calling tool: {tool_call.function.name} with arguments: {tool_call.function.arguments}")
if response.usage.reasoning_tokens and is_thinking:
print(f"
Thinking... ({response.usage.reasoning_tokens} tokens)", end="", flush=True)
if chunk.content and is_thinking:
print("
Final Response:")
is_thinking = False
if chunk.content and not is_thinking:
print(chunk.content, end="", flush=True)
print("
Usage:")
print(response.usage)
print(response.server_side_tool_usage)
print("
Server Side Tool Calls:")
print(response.tool_calls)
This code initializes the Grok AI client, connects to CData Connect AI via MCP using Basic Authentication, and streams the response in real-time. The agent automatically discovers available tools, invokes them to query your live data, and displays both the tool calls and final results.
Run the script to see Grok query your connected data source.
The output shows Grok invoking MCP tools through CData Connect AI and returning live data from your connected source.
π ResultUser can now query live data using natural language through Grok AI.
Combining Grok AI with CData Connect AI delivers AI-powered data access without pipelines or custom integrations. Start your free trial today to see how CData can empower Grok with live, secure access to hundreds of external systems.
Learn more about CData Connect AI or sign up for free trial access:
Free Trial