Build Agents in Relevance AI with Access to Live Databricks Data via CData Connect AI
Relevance AI is an AI automation and agent-building platform that enables organizations to create autonomous workflows powered by natural language reasoning. Users can visually design agents that interact with APIs, databases, and third-party systems to complete everyday business tasks or data operations.
By integrating Relevance AI with CData Connect AI through the built-in MCP (Model Context Protocol) Server, your agents can query, summarize, and act on live Databricks data in real time. This connection bridges Relevance AI intelligent workflow engine with the governed enterprise connectivity of CData Connect AI ensuring every query runs securely against authorized sources without manual data export.
This article outlines the steps to configure Databricks connectivity in Connect AI, register the CData MCP Server in Relevance AI, and build an agent that interacts with live Databricks data.
About Databricks Data Integration
Accessing and integrating live data from Databricks has never been easier with CData. Customers rely on CData connectivity to:
- Access all versions of Databricks from Runtime Versions 9.1 - 13.X to both the Pro and Classic Databricks SQL versions.
- Leave Databricks in their preferred environment thanks to compatibility with any hosting solution.
- Secure authenticate in a variety of ways, including personal access token, Azure Service Principal, and Azure AD.
- Upload data to Databricks using Databricks File System, Azure Blog Storage, and AWS S3 Storage.
While many customers are using CData's solutions to migrate data from different systems into their Databricks data lakehouse, several customers use our live connectivity solutions to federate connectivity between their databases and Databricks. These customers are using SQL Server Linked Servers or Polybase to get live access to Databricks from within their existing RDBMs.
Read more about common Databricks use-cases and how CData's solutions help solve data problems in our blog: What is Databricks Used For? 6 Use Cases.
Getting Started
Step 1: Configure Databricks Connectivity for Relevance AI
Connectivity to Databricks from Relevance AI is made possible through CData Connect AI's Remote MCP Server. To interact with Databricks data from Relevance AI, we start by creating and configuring a Databricks connection in CData Connect AI.
- Log into Connect AI, click Sources, and then click Add Connection
- Select Databricks from the Add Connection panel
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Enter the necessary authentication properties to connect to Databricks.
To connect to a Databricks cluster, set the properties as described below.
Note: The needed values can be found in your Databricks instance by navigating to Clusters, and selecting the desired cluster, and selecting the JDBC/ODBC tab under Advanced Options.
- Server: Set to the Server Hostname of your Databricks cluster.
- HTTPPath: Set to the HTTP Path of your Databricks cluster.
- Token: Set to your personal access token (this value can be obtained by navigating to the User Settings page of your Databricks instance and selecting the Access Tokens tab).
- Click Save & Test
- Navigate to the Permissions tab and update user-based permissions
Add a Personal Access Token
A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from Relevance AI. It is best practice to create a separate PAT for each integration to maintain granular access control.
- Click the gear icon () at the top right of the Connect AI app to open Settings
- On the Settings page, go to the Access Tokens section and click Create PAT
- Give the PAT a descriptive name and click Create
- Copy the token when displayed and store it securely. It will not be shown again
With the Databricks connection configured and a PAT generated, Relevance AI can now connect to Databricks data through the CData MCP Server.
Step 2: Configure Connectivity in Relevance AI
The CData Connect AI MCP endpoint and authorization details are registered within Relevance AI so that agents can call live data from Connect AI.
- Sign in to Relevance AI and create an account if you do not already have one
- From the sidebar, navigate to Agents and then click on New Agent
- Select Build from scratch and name the agent (eg; CData MCP Server)
- Inside the agent editor, select Advanced and then switch to the MCP Server tab
- Click + Add Remote MCP Tools
- In the dialog that appears, fill out the fields as follows:
- URL: https://mcp.cloud.cdata.com/mcp
- Label: Any custom label (eg; cdata_mcp_server)
- Authentication: Select Custom headers
- Add header key:value pair. Combine your email and PAT as email:PAT and encode that string in Base64 and then prefix with the word Basic
- Key: Authorization
- Value: Basic base64(email:PAT)
Click Connect to establish the connection. Relevance AI will verify your credentials and register the CData Connect AI MCP Server for use in agents.
Step 3: Build and Run a Relevance AI Agent with Live Databricks Data
- Switch to the Run tab for your agent
- Enter a task for example, "List the five most recent incidents from ServiceNow"
- The agent will query Connect AI via the MCP endpoint and display live results from Databricks data
With the connection complete, Relevance AI agents can now issue queries, retrieve records, and perform AI-driven tasks over live Databricks data through CData Connect AI MCP Server.
Get CData Connect AI
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