Use Grok to Talk to Your SingleStore Data via CData Connect AI

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 350+ enterprise data sources with Grok AI. Using Connect AI, live SingleStore 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.

Step 1: Configure SingleStore in CData Connect AI

To enable Grok to query live SingleStore data, first create a SingleStore connection in CData Connect AI. This connection is exposed through the CData Remote MCP Server.

1. Log into Connect AI, click Sources, and then click Add Connection.
2. Select "SingleStore" from the Add Connection panel.
3. Enter the required authentication properties.

   The following connection properties are required in order to connect to data.

   • Server: The host name or IP of the server hosting the SingleStore database.
   • Port: The port of the server hosting the SingleStore database.
   • Database (Optional): The default database to connect to when connecting to the SingleStore Server. If this is not set, tables from all databases will be returned.

   Connect Using Standard Authentication

   To authenticate using standard authentication, set the following:

   • User: The user which will be used to authenticate with the SingleStore server.
   • Password: The password which will be used to authenticate with the SingleStore server.

   Connect Using Integrated Security

   As an alternative to providing the standard username and password, you can set IntegratedSecurity to True to authenticate trusted users to the server via Windows Authentication.

   Connect Using SSL Authentication

   You can leverage SSL authentication to connect to SingleStore data via a secure session. Configure the following connection properties to connect to data:

   • SSLClientCert: Set this to the name of the certificate store for the client certificate. Used in the case of 2-way SSL, where truststore and keystore are kept on both the client and server machines.
   • SSLClientCertPassword: If a client certificate store is password-protected, set this value to the store's password.
   • SSLClientCertSubject: The subject of the TLS/SSL client certificate. Used to locate the certificate in the store.
   • SSLClientCertType: The certificate type of the client store.
   • SSLServerCert: The certificate to be accepted from the server.

   Connect Using SSH Authentication

   Using SSH, you can securely login to a remote machine. To access SingleStore data via SSH, configure the following connection properties:

   • SSHClientCert: Set this to the name of the certificate store for the client certificate.
   • SSHClientCertPassword: If a client certificate store is password-protected, set this value to the store's password.
   • SSHClientCertSubject: The subject of the TLS/SSL client certificate. Used to locate the certificate in the store.
   • SSHClientCertType: The certificate type of the client store.
   • SSHPassword: The password that you use to authenticate with the SSH server.
   • SSHPort: The port used for SSH operations.
   • SSHServer: The SSH authentication server you are trying to authenticate against.
   • SSHServerFingerPrint: The SSH Server fingerprint used for verification of the host you are connecting to.
   • SSHUser: Set this to the username that you use to authenticate with the SSH server.
   Click Create & Test.
4. Open the Permissions tab and configure user access.

Add a Personal Access Token

A Personal Access Token (PAT) authenticates MCP requests from Agno to CData Connect AI.

1. Open Settings and navigate to Access Tokens.
2. Click Create PAT.
3. Save the generated token securely.

Step 2: Install required dependencies

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

Step 3: Generate an xAI API key

1. Create or login to xAI account
2. Open xAI API console
3. Navigate to API Keys

4. Click on create API key

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.

Step 4: Connect to CData Connect AI

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.

Query Results

The output shows Grok invoking MCP tools through CData Connect AI and returning live data from your connected source.

User can now query live data using natural language through Grok AI.

Build agentic workflows with Grok and CData Connect 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 350+ external systems.