Use Grok to Talk to Your Salesforce 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 Salesforce 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.
About Salesforce Data Integration
Accessing and integrating live data from Salesforce has never been easier with CData. Customers rely on CData connectivity to:
- Access to custom entities and fields means Salesforce users get access to all of Salesforce.
- Create atomic and batch update operations.
- Read, write, update, and delete their Salesforce data.
- Leverage the latest Salesforce features and functionalities with support for SOAP API versions 30.0.
- See improved performance based on SOQL support to push complex queries down to Salesforce servers.
- Use SQL stored procedures to perform actions like creating, retrieving, aborting, and deleting jobs, uploading and downloading attachments and documents, and more.
Users frequently integrate Salesforce data with:
- other ERPs, marketing automation, HCMs, and more.
- preferred data tools like Power BI, Tableau, Looker, and more.
- databases and data warehouses.
For more information on how CData solutions work with Salesforce, check out our Salesforce integration page.
Getting Started
Step 1: Configure Salesforce in CData Connect AI
To enable Grok to query live Salesforce data, first create a Salesforce connection in CData Connect AI. This connection is exposed through the CData Remote MCP Server.
-
Log into Connect AI, click Sources, and then click Add Connection.
-
Select "Salesforce" from the Add Connection panel.
-
Authenticate using OAuth.
-
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.
- Open Settings and navigate to Access Tokens.
- Click Create PAT.
-
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
- Create or login to xAI account
- Open xAI API console
- Navigate to API Keys
- 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.