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

This article explains how to configure SingleStore 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 SingleStore data from Dify.

Step 1: Configure SingleStore connectivity for Dify

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

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

2. Select SingleStore from the Add Connection panel

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

   The following connection properties are required in order to connect to data.

   • Server: The host name or IP of the server hosting the SingleStore database.
   • Port: The port of the server hosting the SingleStore database.
   • Database (Optional): The default database to connect to when connecting to the SingleStore Server. If this is not set, tables from all databases will be returned.

   Connect Using Standard Authentication

   To authenticate using standard authentication, set the following:

   • User: The user which will be used to authenticate with the SingleStore server.
   • Password: The password which will be used to authenticate with the SingleStore server.

   Connect Using Integrated Security

   As an alternative to providing the standard username and password, you can set IntegratedSecurity to True to authenticate trusted users to the server via Windows Authentication.

   Connect Using SSL Authentication

   You can leverage SSL authentication to connect to SingleStore data via a secure session. Configure the following connection properties to connect to data:

   • SSLClientCert: Set this to the name of the certificate store for the client certificate. Used in the case of 2-way SSL, where truststore and keystore are kept on both the client and server machines.
   • SSLClientCertPassword: If a client certificate store is password-protected, set this value to the store's password.
   • SSLClientCertSubject: The subject of the TLS/SSL client certificate. Used to locate the certificate in the store.
   • SSLClientCertType: The certificate type of the client store.
   • SSLServerCert: The certificate to be accepted from the server.

   Connect Using SSH Authentication

   Using SSH, you can securely login to a remote machine. To access SingleStore data via SSH, configure the following connection properties:

   • SSHClientCert: Set this to the name of the certificate store for the client certificate.
   • SSHClientCertPassword: If a client certificate store is password-protected, set this value to the store's password.
   • SSHClientCertSubject: The subject of the TLS/SSL client certificate. Used to locate the certificate in the store.
   • SSHClientCertType: The certificate type of the client store.
   • SSHPassword: The password that you use to authenticate with the SSH server.
   • SSHPort: The port used for SSH operations.
   • SSHServer: The SSH authentication server you are trying to authenticate against.
   • SSHServerFingerPrint: The SSH Server fingerprint used for verification of the host you are connecting to.
   • SSHUser: Set this to the username that you use to authenticate with the SSH server.
   
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 SingleStore connection configured and a PAT generated, Dify can now connect to SingleStore 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 SingleStore data from Dify

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

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

Get started with CData Connect AI

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