Integrate Trae with Live CSV Data via CData Connect AI

Trae is an AI-powered integrated development environment (IDE) that pairs a familiar editor with agent modes such as Builder and SOLO. It supports the Model Context Protocol (MCP), so you can add external tools and data sources and give the agent access to live data.

By integrating Trae with CData Connect AI through the built-in MCP Server, Trae gains governed, real-time access to live CSV data. You can list catalogs, explore schemas, and query records from CSV data using natural language prompts, with all data access running securely against authorized sources.

This article explains how to configure CSV connectivity in Connect AI, generate the required personal access token, install Trae, add the Connect AI MCP Server, configure an LLM model, and verify the integration by querying live CSV data from the Trae agent.

Step 1: Configure CSV connectivity for Trae

Connectivity to CSV from Trae is made possible through Connect AI's Remote MCP Server. To interact with CSV data from Trae, start by creating and configuring a CSV connection in Connect AI.

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

2. Select CSV from the Add Connection panel

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

   Connecting to Local or Cloud-Stored (Box, Google Drive, Amazon S3, SharePoint) CSV Files

   CData Drivers let you work with CSV files stored locally and stored in cloud storage services like Box, Amazon S3, Google Drive, or SharePoint, right where they are.

   Setting connection properties for local files

   Set the URI property to local folder path.

   Setting connection properties for files stored in Amazon S3

   To connect to CSV file(s) within Amazon S3, set the URI property to the URI of the Bucket and Folder where the intended CSV files exist. In addition, at least set these properties:

   • AWSAccessKey: AWS Access Key (username)
   • AWSSecretKey: AWS Secret Key

   Setting connection properties for files stored in Box

   To connect to CSV file(s) within Box, set the URI property to the URI of the folder that includes the intended CSV file(s). Use the OAuth authentication method to connect to Box.

   Dropbox

   To connect to CSV file(s) within Dropbox, set the URI proprerty to the URI of the folder that includes the intended CSV file(s). Use the OAuth authentication method to connect to Dropbox. Either User Account or Service Account can be used to authenticate.

   SharePoint Online (SOAP)

   To connect to CSV file(s) within SharePoint with SOAP Schema, set the URI proprerty to the URI of the document library that includes the intended CSV file. Set User, Password, and StorageBaseURL.

   SharePoint Online REST

   To connect to CSV file(s) within SharePoint with REST Schema, set the URI proprerty to the URI of the document library that includes the intended CSV file. StorageBaseURL is optional. If not set, the driver will use the root drive. OAuth is used to authenticate.

   Google Drive

   To connect to CSV file(s) within Google Drive, set the URI property to the URI of the folder that includes the intended CSV file(s). Use the OAuth authentication method to connect and set InitiateOAuth to GETANDREFRESH.

   
4. Click Save & Test
5. 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 Trae. It is best practice to create a separate PAT for each integration to maintain granular access control.

1. Click the gear icon () at the top right of the Connect AI app to open Settings
2. On the Settings page, go to the Access Tokens section and click Create PAT
3. Give the PAT a descriptive name and click Create

4. Copy the token when displayed and store it securely. It will not be shown again

With the CSV connection configured and a PAT generated, Trae can now connect to CSV data through Connect AI.

Step 2: Install Trae and configure the Connect AI MCP Server

Next, install Trae, add the Connect AI Remote MCP Server, and configure an LLM model so the agent can discover and call live data tools through Connect AI.

1. Download and install the Trae IDE, then launch the application
2. Switch to SOLO mode using the toggle at the top left, or press Ctrl + Alt + \
3. Click Toggle AI Sidebar to open the chat panel
4. Open Settings, then select MCP from the left menu
5. Click Add Manually
6. In the Configure Manually dialog, paste the following configuration and click Confirm:

   {
     "mcpServers": {
       "cdata-connect-ai": {
         "type": "streamable-http",
         "url": "https://mcp.cloud.cdata.com/mcp",
         "headers": {
           "Authorization": "Basic your_base64_encoded_email_PAT"
         }
       }
     }
   }
   		

   Note: Trae will use Basic authentication with Connect AI. Combine your Connect AI user email and the PAT you created earlier in the format email:PAT, base64 encode the combined string, and prefix it with Basic. For example, given [email protected]:ABC123...XYZ789, the Authorization header value becomes something like: Basic dXNlckBkb21haW4uY29tOkFCQzEyMy4uLlhZWjc4OQ==

   

Configure an LLM model

Trae requires at least one LLM model to power the agent's reasoning. Add a model so the agent can interpret prompts and call MCP tools through Connect AI.

1. Return to Settings and select Models
2. Click Add Model, choose a provider such as OpenAI, Anthropic, or Google, select a model, enter your API key, and click Add Model

With the MCP server added and an LLM model configured, Trae is ready to query live CSV data through Connect AI.

Step 3: Query live CSV data from Trae

With the integration complete, use the Trae agent to interact with live CSV data through natural language prompts handled by the configured LLM.

1. In the chat panel, type @ and select Builder with MCP. Confirm that cdata-connect-ai is listed under Tools - MCP
2. Enter a prompt to interact with your data, for example:
   • List all catalogs in cdata-connect-ai
   • Show the available schemas and tables for CSV
   • Query the top 5 records from a table in CSV data
3. Trae calls the Connect AI MCP Server and returns live results from CSV data

At this point, the Trae agent communicates with the Connect AI MCP Server and retrieves live CSV data through remote MCP tools directly from the IDE.

Get CData Connect AI

To access hundreds of SaaS, big data, and NoSQL sources directly from your cloud applications, try CData Connect AI today. Download a free 14-day trial of CData Connect AI, and our Support Team is available to help with any questions you have.