Connecting Mastra with IBM Cloud Object Storage 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 IBM Cloud Object Storage data in real time.
Prerequisites
Before starting, make sure you have:
- A CData Connect AI account
- Node.js 18+ and npm installed
- A working Mastra project (created via npm create mastra@latest)
- Access to IBM Cloud Object Storage
Credentials checklist
Ensure you have these credentials ready for the connection:
- USERNAME: Your CData email login
- PAT: Connect AI, go to Settings and click on Access Tokens (copy once)
- MCP_BASE_URL: https://mcp.cloud.cdata.com/mcp
Step 1: Configure IBM Cloud Object Storage connectivity for Mastra
Connectivity to IBM Cloud Object Storage from Mastra is made possible through CData Connect AI Remote MCP. To interact with IBM Cloud Object Storage data from Mastra, we start by creating and configuring a IBM Cloud Object Storage connection in CData Connect AI.
- Log into Connect AI, click Sources, and then click Add Connection
- Select "IBM Cloud Object Storage" from the Add Connection panel
-
Enter the necessary authentication properties to connect to IBM Cloud Object Storage.
Register a New Instance of Cloud Object Storage
If you do not already have Cloud Object Storage in your IBM Cloud account, follow the procedure below to install an instance of SQL Query in your account:
- Log in to your IBM Cloud account.
- Navigate to the page, choose a name for your instance and click Create. You will be redirected to the instance of Cloud Object Storage you just created.
Connecting using OAuth Authentication
There are certain connection properties you need to set before you can connect. You can obtain these as follows:
API Key
To connect with IBM Cloud Object Storage, you need an API Key. You can obtain this as follows:
- Log in to your IBM Cloud account.
- Navigate to the Platform API Keys page.
- On the middle-right corner click "Create an IBM Cloud API Key" to create a new API Key.
- In the pop-up window, specify the API Key name and click "Create". Note the API Key as you can never access it again from the dashboard.
Cloud Object Storage CRN
If you have multiple accounts, specify the CloudObjectStorageCRN explicitly. To find the appropriate value, you can:
- Query the Services view. This will list your IBM Cloud Object Storage instances along with the CRN for each.
- Locate the CRN directly in IBM Cloud. To do so, navigate to your IBM Cloud Dashboard. In the Resource List, Under Storage, select your Cloud Object Storage resource to get its CRN.
Connecting to Data
You can now set the following to connect to data:
- InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to avoid repeating the OAuth exchange and manually setting the OAuthAccessToken.
- ApiKey: Set this to your API key which was noted during setup.
- CloudObjectStorageCRN (Optional): Set this to the cloud object storage CRN you want to work with. While the connector attempts to retrieve this automatically, specifying this explicitly is recommended if you have more than Cloud Object Storage account.
When you connect, the connector completes the OAuth process.
- Extracts the access token and authenticates requests.
- Saves OAuth values in OAuthSettingsLocation to be persisted across connections.
- Click Save & Test
-
Navigate to the Permissions tab in the Add IBM Cloud Object Storage 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.
- Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
- On the Settings page, go to the Access Tokens section and click Create PAT.
-
Give the PAT a name and click Create.
- 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 IBM Cloud Object Storage 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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