Connecting Mastra with HubDB Data via CData Connect AI MCP Server

Mastra is designed for developers and enterprise teams building intelligent, composable AI agents. Its modular framework and declarative architecture make it simple to orchestrate agents, integrate LLMs, and automate data-driven workflows. But when agents need to work with data beyond their local memory or predefined APIs, many implementations rely on custom middleware or scheduled syncs to copy data from external systems into local stores. This approach adds complexity, increases maintenance overhead, introduces latency, and limits the real-time potential of your agents.

CData Connect AI bridges this gap with live, direct connectivity to more than 300 enterprise applications, databases, ERPs, and analytics platforms. Through CData's remote Model Context Protocol (MCP) Server, Mastra agents can securely query, read, and act on real-time data without replication. The result is grounded responses, faster reasoning, and automated decision-making across systems all with stronger governance and fewer moving parts.

This article outlines the steps required to configure CData Connect AI MCP connectivity, register the MCP server in Mastra Studio, and build an agent that queries live HubDB data in real time.

Prerequisites

Before starting, make sure you have:

1. A CData Connect AI account
2. Node.js 18+ and npm installed
3. A working Mastra project (created via npm create mastra@latest)
4. Access to HubDB

Credentials checklist

Ensure you have these credentials ready for the connection:

1. USERNAME: Your CData email login
2. PAT: Connect AI, go to Settings and click on Access Tokens (copy once)
3. MCP_BASE_URL: https://mcp.cloud.cdata.com/mcp

Step 1: Configure HubDB connectivity for Mastra

Connectivity to HubDB from Mastra is made possible through CData Connect AI Remote MCP. To interact with HubDB data from Mastra, we start by creating and configuring a HubDB connection in CData Connect AI.

1. Log into Connect AI, click Sources, and then click Add Connection

2. Select "HubDB" from the Add Connection panel

3. Enter the necessary authentication properties to connect to HubDB.

   There are two authentication methods available for connecting to HubDB data source: OAuth Authentication with a public HubSpot application and authentication with a Private application token.

   Using a Custom OAuth App

   AuthScheme must be set to "OAuth" in all OAuth flows. Be sure to review the Help documentation for the required connection properties for you specific authentication needs (desktop applications, web applications, and headless machines).

   Follow the steps below to register an application and obtain the OAuth client credentials:

   1. Log into your HubSpot app developer account.
      • Note that it must be an app developer account. Standard HubSpot accounts cannot create public apps.
   2. On the developer account home page, click the Apps tab.
   3. Click Create app.
   4. On the App info tab, enter and optionally modify values that are displayed to users when they connect. These values include the public application name, application logo, and a description of the application.
   5. On the Auth tab, supply a callback URL in the "Redirect URLs" box.
      • If you're creating a desktop application, set this to a locally accessible URL like http://localhost:33333.
      • If you are creating a Web application, set this to a trusted URL where you want users to be redirected to when they authorize your application.
   6. Click Create App. HubSpot then generates the application, along with its associated credentials.
   7. On the Auth tab, note the Client ID and Client secret. You will use these later to configure the driver.

   8. Under Scopes, select any scopes you need for your application's intended functionality.

      A minimum of the following scopes is required to access tables:

      • hubdb
      • oauth
      • crm.objects.owners.read
   9. Click Save changes.
   10. Install the application into a production portal with access to the features that are required by the integration.
       • Under "Install URL (OAuth)", click Copy full URL to copy the installation URL for your application.
       • Navigate to the copied link in your browser. Select a standard account in which to install the application.
       • Click Connect app. You can close the resulting tab.

   Using a Private App

   To connect using a HubSpot private application token, set the AuthScheme property to "PrivateApp."

   You can generate a private application token by following the steps below:

   1. In your HubDB account, click the settings icon (the gear) in the main navigation bar.
   2. In the left sidebar menu, navigate to Integrations > Private Apps.
   3. Click Create private app.
   4. On the Basic Info tab, configure the details of your application (name, logo, and description).
   5. On the Scopes tab, select Read or Write for each scope you want your private application to be able to access.
   6. A minimum of hubdb and crm.objects.owners.read is required to access tables.
   7. After you are done configuring your application, click Create app in the top right.
   8. Review the info about your application's access token, click Continue creating, and then Show token.
   9. Click Copy to copy the private application token.

   To connect, set PrivateAppToken to the private application token you retrieved.

   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add HubDB Connection page and update the User-based permissions.

Add a Personal Access Token

A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from Mastra. It is best practice to create a separate PAT for each service to maintain granularity of access.

1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create.
4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, we are ready to connect to HubDB data from Mastra.

Step 2: Set up the Mastra project

• Open a terminal and navigate to your desired folder
• Create a new project:

  npm create mastra@latest


• Open the folder in VS Code
• Install the required Mastra dependencies:

  npm install @mastra/core @mastra/libsql @mastra/memory

• Then install the MCP integration package separately:

  npm install @mastra/mcp

Step 3: Configure environment variables

Create a .env file at the project root with the following keys:

OPENAI_API_KEY=sk-...
[email protected]
CDATA_CONNECT_AI_PASSWORD=your_PAT

Restart your dev server after saving changes:

npm run dev

Step 4: Add the CData Connect AI agent

Create a file src/mastra/agents/connect-ai-agent.ts with the following code:

import { Agent } from "@mastra/core/agent";
import { Memory } from "@mastra/memory";
import { LibSQLStore } from "@mastra/libsql";
import { MCPClient } from "@mastra/mcp";

const mcpClient = new MCPClient({
  servers: {
    cdataConnectAI: {
      url: new URL("https://connect.cdata.com/mcp/"),
      requestInit: {
        headers: {
          Authorization: `Basic ${Buffer.from(
            `${process.env.CDATA_CONNECT_AI_USER}:${process.env.CDATA_CONNECT_AI_PASSWORD}`
          ).toString("base64")}`,
        },
      },
    },
  },
});

export const connectAIAgent = new Agent({
  name: "Connect AI Agent",
  instructions: "You are a data exploration and analysis assistant with access to CData Connect AI.",
  model: "openai/gpt-4o-mini",
  tools: await mcpClient.getTools(),
  memory: new Memory({
    storage: new LibSQLStore({ url: "file:../mastra.db" }),
  }),
});

Step 5: Update index.ts to register the agent

Replace the contents of src/mastra/index.ts with:

import { Mastra } from "@mastra/core/mastra";
import { PinoLogger } from "@mastra/loggers";
import { LibSQLStore } from "@mastra/libsql";
import { connectAIAgent } from "./agents/connect-ai-agent.js";

export const mastra = new Mastra({
  agents: { connectAIAgent },
  storage: new LibSQLStore({ url: "file:../mastra.db" }),
  logger: new PinoLogger({ name: "Mastra", level: "info" }),
  observability: { default: { enabled: true } },
});

Step 6: Run and verify the connection

Start your Mastra server:

npm run dev



Step 7: Run a live query in Mastra Studio

In Mastra Studio, open the chat interface and enter one of the following sample prompts:

List available catalogs from my connected data sources.



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