Use Manus AI to Talk to Your Azure Data Lake Storage Data via CData Connect AI

Manus AI is an autonomous AI agent platform that helps users accomplish complex tasks through natural language from browsing the web to executing code and interacting with external services. When combined with CData Connect AI remote MCP, users can leverage Manus AI to interact with their Azure Data Lake Storage data in real-time, without any data replication.

This article explains how to connect to Azure Data Lake Storage using the CData Connect AI MCP Server and configure Manus AI to conversationally explore (or Vibe Query) their Azure Data Lake Storage data. With Connect AI, users can build AI agents with access to live Azure Data Lake Storage data, plus hundreds of other sources.

Step 1: Configure Azure Data Lake Storage connectivity for Manus AI

Connectivity to Azure Data Lake Storage from Manus AI is made possible through CData Connect AI Remote MCP. To interact with Azure Data Lake Storage data from Manus AI, we start by creating and configuring a Azure Data Lake Storage connection in CData Connect AI.

1. Log into Connect AI, click Connections and click Add Connection
2. Select "Azure Data Lake Storage" from the Add Connection panel
3. Enter the necessary authentication properties to connect to Azure Data Lake Storage.

   Authenticating to a Gen 1 DataLakeStore Account

   Gen 1 uses OAuth 2.0 in Entra ID (formerly Azure AD) for authentication.

   For this, an Active Directory web application is required. You can create one as follows:

   1. Sign in to your Azure Account through the .
   2. Select "Entra ID" (formerly Azure AD).
   3. Select "App registrations".
   4. Select "New application registration".
   5. Provide a name and URL for the application. Select Web app for the type of application you want to create.
   6. Select "Required permissions" and change the required permissions for this app. At a minimum, "Azure Data Lake" and "Windows Azure Service Management API" are required.
   7. Select "Key" and generate a new key. Add a description, a duration, and take note of the generated key. You won't be able to see it again.

   To authenticate against a Gen 1 DataLakeStore account, the following properties are required:

   • Schema: Set this to ADLSGen1.
   • Account: Set this to the name of the account.
   • OAuthClientId: Set this to the application Id of the app you created.
   • OAuthClientSecret: Set this to the key generated for the app you created.
   • TenantId: Set this to the tenant Id. See the property for more information on how to acquire this.
   • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.

   Authenticating to a Gen 2 DataLakeStore Account

   To authenticate against a Gen 2 DataLakeStore account, the following properties are required:

   • Schema: Set this to ADLSGen2.
   • Account: Set this to the name of the account.
   • FileSystem: Set this to the file system which will be used for this account.
   • AccessKey: Set this to the access key which will be used to authenticate the calls to the API. See the property for more information on how to acquire this.
   • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.
   Click Save & Test
4. Navigate to the Permissions tab in the Add Azure Data Lake Storage Connection page and update the User-based permissions.

Add a Personal Access Token

A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from Manus AI. It is best practice to create a separate PAT for each service to maintain granularity of access.

1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create.
4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, we are ready to connect to Azure Data Lake Storage data from Manus AI.

Step 2: Get started with Manus AI

Navigate to Manus and sign in to your Manus AI account. Once logged in, you are ready to configure the CData Connect AI MCP Server as a custom connector.

Step 3: Add the CData Connect AI MCP Server as a connector

Manus AI supports connecting to external MCP servers via its Connectors settings. There are two methods to add the CData Connect AI MCP Server: Import by JSON or Direct Configuration. Both methods are explained below.

1. In Manus AI, click on the profile icon and navigate to Settings
2. Go to the Connectors section and click Add Connectors
3. Locate Custom MCP
4. Click Add custom MCP to select the configuration options

Option A: Import by JSON

Use this method to quickly configure the MCP Server by pasting a JSON configuration snippet.

1. Select Import by JSON from the connector setup options.
2. Paste the following JSON into the configuration field, replacing the placeholder values with your Connect AI credentials:

   {
     "mcpServers": {
       "cdata-connect-ai": {
         "transport": "sse",
         "url": "https://mcp.cloud.cdata.com/mcp",
         "headers": {
           "Authorization": "Basic USER_NAME:YOUR_CONNECTAI_PAT;"
         }
       }
     }
   }
       

   Replace url with the Connect AI MCP URL, USER_NAME with your Connect AI email address, and YOUR_CONNECTAI_PAT with the Personal Access Token created in Step 1.
3. Click Import to apply the configuration.

Option B: Direct Configuration

Use this method to manually enter the MCP Server connection properties through the Manus AI interface.

1. Select Direct Configuration from the connector setup options.
2. Fill in the following fields:
   • Server Name: CData Connect AI
   • Transport Type: HTTP
   • Server URL: https://mcp.cloud.cdata.com/mcp
   • Custom Headers: Add a header with the name Authorization and the value Basic Base64Encoded(username:pat), replacing the placeholder with your Base64-encoded Connect AI email and PAT combination.
   
3. Optionally, enter a Note to provide Manus AI with instructions on how and when to use this MCP connector.
4. Click Save to establish the connection to the CData Connect AI MCP Server. Once saved, the connector will appear as active in your Connectors list.

Step 4: Query your Azure Data Lake Storage data using natural language

With the CData Connect AI MCP configured in Manus AI, users can now interact with their Azure Data Lake Storage data using natural language in any new Manus AI chat session.

1. Open a new chat in Manus AI.
2. Start asking questions about the Azure Data Lake Storage data. For example:
   • Show me all customers from the last 30 days
   • What are my top performing products?
   • Analyze sales trends for Q4
   • List all active projects with their current status
3. Manus AI will use the CData Connect AI MCP Server to query your Azure Data Lake Storage data in real-time and provide responses based on live data.

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