![]() |
VOOZH | about |
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 Adobe Commerce data in real time.
Before starting, make sure you have:
Ensure you have these credentials ready for the connection:
Connectivity to Adobe Commerce from Mastra is made possible through CData Connect AI Remote MCP. To interact with Adobe Commerce data from Mastra, we start by creating and configuring a Adobe Commerce connection in CData Connect AI.
Adobe Commerce uses the OAuth 1 authentication standard. To connect to the Adobe Commerce REST API, obtain values for the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties by registering an app with your Adobe Commerce system. See the "Getting Started" section in the help documentation for a guide to obtaining the OAuth values and connecting.
You will also need to provide the URL to your Adobe Commerce system. The URL depends on whether you are using the Adobe Commerce REST API as a customer or administrator.
Customer: To use Adobe Commerce as a customer, make sure you have created a customer account in the Adobe Commerce homepage. To do so, click Account -> Register. You can then set the URL connection property to the endpoint of your Adobe Commerce system.
Administrator: To access Adobe Commerce as an administrator, set CustomAdminPath instead. This value can be obtained in the Advanced settings in the Admin menu, which can be accessed by selecting System -> Configuration -> Advanced -> Admin -> Admin Base URL.
If the Use Custom Admin Path setting on this page is set to YES, the value is inside the Custom Admin Path text box; otherwise, set the CustomAdminPath connection property to the default value, which is "admin".
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.
With the connection configured and a PAT generated, we are ready to connect to Adobe Commerce data from Mastra.
npm create mastra@latest
npm install @mastra/core @mastra/libsql @mastra/memory
npm install @mastra/mcp
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
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" }),
}),
});
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 } },
});
Start your Mastra server:
npm run devπ Start your Mastra server
In Mastra Studio, open the chat interface and enter one of the following sample prompts:
List available catalogs from my connected data sources.π Run QUery in Mastra Studio
Mastra and CData Connect AI together enable powerful AI-driven workflows where agents have live access to enterprise data and act intelligently without sync pipelines or manual integration logic.
Start your free trial today to see how CData can empower Mastra with live, secure access to hundreds of external systems.
Learn more about CData Connect AI or sign up for free trial access:
Free Trial