Use Manus AI to Talk to Your Bitbucket 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 Bitbucket data in real-time, without any data replication.

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

Step 1: Configure Bitbucket connectivity for Manus AI

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

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

   For most queries, you must set the Workspace. The only exception to this is the Workspaces table, which does not require this property to be set, as querying it provides a list of workspace slugs that can be used to set Workspace. To query this table, you must set Schema to 'Information' and execute the query SELECT * FROM Workspaces>.

   Setting Schema to 'Information' displays general information. To connect to Bitbucket, set these parameters:

   • Schema: To show general information about a workspace, such as its users, repositories, and projects, set this to Information. Otherwise, set this to the schema of the repository or project you are querying. To get a full set of available schemas, query the sys_schemas table.
   • Workspace: Required if you are not querying the Workspaces table. This property is not required for querying the Workspaces table, as that query only returns a list of workspace slugs that can be used to set Workspace.

   Authenticating to Bitbucket

   Bitbucket supports OAuth authentication only. To enable this authentication from all OAuth flows, you must create a custom OAuth application, and set AuthScheme to OAuth.

   Be sure to review the Help documentation for the required connection properties for you specific authentication needs (desktop applications, web applications, and headless machines).

   Creating a custom OAuth application

   From your Bitbucket account:

   1. Go to Settings (the gear icon) and select Workspace Settings.
   2. In the Apps and Features section, select OAuth Consumers.
   3. Click Add Consumer.
   4. Enter a name and description for your custom application.
   5. Set the callback URL:
      • For desktop applications and headless machines, use http://localhost:33333 or another port number of your choice. The URI you set here becomes the CallbackURL property.
      • For web applications, set the callback URL to a trusted redirect URL. This URL is the web location the user returns to with the token that verifies that your application has been granted access.
   6. If you plan to use client credentials to authenticate, you must select This is a private consumer. In the driver, you must set AuthScheme to client.
   7. Select which permissions to give your OAuth application. These determine what data you can read and write with it.
   8. To save the new custom application, click Save.
   9. After the application has been saved, you can select it to view its settings. The application's Key and Secret are displayed. Record these for future use. You will use the Key to set the OAuthClientId and the Secret to set the OAuthClientSecret.
   Click Save & Test
4. Navigate to the Permissions tab in the Add Bitbucket 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 Bitbucket 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 Bitbucket data using natural language

With the CData Connect AI MCP configured in Manus AI, users can now interact with their Bitbucket 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 Bitbucket 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 Bitbucket data in real-time and provide responses based on live data.

Get CData Connect AI

To get live data access to hundreds of SaaS, big data, and NoSQL sources directly from your cloud applications, try CData Connect AI today!