Connecting Mastra with HCL Domino 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 HCL Domino 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 HCL Domino

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 HCL Domino connectivity for Mastra

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

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

2. Select "HCL Domino" from the Add Connection panel

3. Enter the necessary authentication properties to connect to HCL Domino.

   Connecting to Domino

   To connect to Domino data, set the following properties:

   • URL: The host name or IP of the server hosting the Domino database. Include the port of the server hosting the Domino database. For example: http://sampleserver:1234/
   • DatabaseScope: The name of a scope in the Domino Web UI. The driver exposes forms and views for the schema governed by the specified scope. In the Domino Admin UI, select the Scopes menu in the sidebar. Set this property to the name of an existing scope.

   Authenticating with Domino

   Domino supports authenticating via login credentials or an Entra ID (formerly Azure AD) OAuth application:

   Login Credentials

   To authenticate with login credentials, set the following properties:

   • AuthScheme: Set this to "OAuthPassword"
   • User: The username of the authenticating Domino user
   • Password: The password associated with the authenticating Domino user

   The driver uses the login credentials to automatically perform an OAuth token exchange.

   EntraID (formerly AzureAD)

   This authentication method uses Entra ID (formerly Azure AD) as an IdP to obtain a JWT token. You need to create a custom OAuth application in Entra ID (formerly Azure AD) and configure it as an IdP. To do so, follow the instructions in the Help documentation. Then set the following properties:

   • AuthScheme: Set this to "EntraID (formerly AzureAD)"
   • InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to avoid repeating the OAuth exchange and manually setting the OAuthAccessToken.
   • OAuthClientId: The Client ID obtained when setting up the custom OAuth application.
   • OAuthClientSecret: The Client secret obtained when setting up the custom OAuth application.
   • CallbackURL: The redirect URI defined when you registered your app. For example: https://localhost:33333
   • AzureTenant: The Microsoft Online tenant being used to access data. Supply either a value in the form companyname.microsoft.com or the tenant ID.

     The tenant ID is the same as the directory ID shown in the Azure Portal's Entra ID (formerly Azure AD) > Properties page.

   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add HCL Domino 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 HCL Domino 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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