Integrate Dify with Live XML Data via CData Connect AI

Dify is an open source platform for building production-ready agentic workflows, chatbots, and other LLM applications. It includes built-in, two-way support for the model context protocol (MCP), allowing you to register remote MCP servers as tools in the platform to add external data sources and give your agents access to live data.

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

This article explains how to configure XML connectivity in Connect AI, generate the required personal access token, register the Connect AI MCP Server as a tool in Dify, add it to an agent application, and verify the integration by querying live XML data from Dify.

Step 1: Configure XML connectivity for Dify

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

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

2. Select XML from the Add Connection panel

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

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

   CData Drivers let you work with XML 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 XML file(s) within Amazon S3, set the URI property to the URI of the Bucket and Folder where the intended XML 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 XML file(s) within Box, set the URI property to the URI of the folder that includes the intended XML file(s). Use the OAuth authentication method to connect to Box.

   Dropbox

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

   SharePoint Online REST

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

   Google Drive

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

   The DataModel property is the controlling property over how your data is represented into tables and toggles the following basic configurations.

   • Document (default): Model a top-level, document view of your XML data. The data provider returns nested elements as aggregates of data.
   • FlattenedDocuments: Implicitly join nested documents and their parents into a single table.
   • Relational: Return individual, related tables from hierarchical data. The tables contain a primary key and a foreign key that links to the parent document.

   See the Modeling XML Data chapter for more information on configuring the relational representation. You will also find the sample data used in the following examples. The data includes entries for people, the cars they own, and various maintenance services performed on those cars.

   
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 Dify. 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 XML connection configured and a PAT generated, Dify can now connect to XML data through Connect AI.

Step 2: Register the Connect AI MCP Server in Dify

Next, register the Connect AI Remote MCP Server as a tool in Dify so your agents and workflows can discover and call live data tools through Connect AI.

1. Log into Dify, or open your self-hosted Dify instance (version 1.6.0 or later, which includes built-in MCP support)
2. Navigate to the Integrations page, select Tools and click MCP tab

3. Click Add MCP Server (HTTP) and enter the following details:
   • Server URL: https://mcp.cloud.cdata.com/mcp
   • Name Icon: Give a descriptive name, for example, CData Connect AI
   • Server Identifier: A unique identifier, for example, cdata-connect-ai
   • Headers: Add an Authorization header with the value Basic your_base64_encoded_email_PAT

   Note: Dify 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.

4. Click Add & Authorize. Dify connects to the Connect AI MCP Server and lists the available tools

With the MCP server registered, the Connect AI tools are available to any agent application or workflow in your Dify workspace.

Step 3: Query live XML data from Dify

With the integration complete, build an agent application in Dify and interact with live XML data through natural language prompts.

1. From the Dify Studio page, click Create from Blank and select Agent as the application type
2. In the agent configuration, click Add under the Tools section and select the Connect AI MCP tools registered in Step 2
3. Select an LLM provider and model for the agent so it can interpret prompts and call MCP tools
4. In the preview panel, type a prompt in the chat input, for example:
   • Use the cdata-connect-ai tools to list all available catalogs
   • Show the available schemas and tables for XML
   • Query the top 5 records from a table in XML
5. The Dify agent calls the Connect AI MCP Server and returns live results from XML data

At this point, Dify communicates with the Connect AI MCP Server and retrieves live XML data through remote MCP tools directly from your agentic workflows.

Get started with CData Connect AI

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