Integrate Dify with Live Azure Analysis Services 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 Azure Analysis Services data. You can list catalogs, explore schemas, and query records from Azure Analysis Services data using natural language prompts, with all data access running securely against authorized sources.

This article explains how to configure Azure Analysis Services 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 Azure Analysis Services data from Dify.

Step 1: Configure Azure Analysis Services connectivity for Dify

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

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

2. Select Azure Analysis Services from the Add Connection panel

3. Enter the necessary authentication properties to connect to Azure Analysis Services.

   To connect to Azure Analysis Services, set the Url property to a valid server, for instance, asazure://southcentralus.asazure.windows.net/server, in addition to authenticating. Optionally, set Database to distinguish which Azure database on the server to connect to.

   Azure Analysis Services uses the OAuth authentication standard. OAuth requires the authenticating user to interact with Azure Analysis Services using the browser. You can connect without setting any connection properties for your user credentials. See the Help documentation for more information.

   
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 Azure Analysis Services connection configured and a PAT generated, Dify can now connect to Azure Analysis Services 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 Azure Analysis Services data from Dify

With the integration complete, build an agent application in Dify and interact with live Azure Analysis Services 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 Azure Analysis Services
   • Query the top 5 records from a table in Azure Analysis Services
5. The Dify agent calls the Connect AI MCP Server and returns live results from Azure Analysis Services data

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

Get started with 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.