Access Live Bitbucket Data in Emergent via CData Connect AI

Emergent is an AI-powered development platform that lets users describe what they want to build and have an autonomous agent generate full-stack web applications in real time. Agents can connect to external tools and data sources through MCP to retrieve live data and power their outputs.

By integrating Emergent with CData Connect AI through the built-in MCP (Model Context Protocol) Server, Emergent agents gain governed, real-time access to live Bitbucket data. This enables agents to query, analyze, and visualize Bitbucket data: either by calling MCP tools directly during a session, or by generating a full application wired to live data, all without manual data exports or custom integration code.

This article outlines the steps to configure Bitbucket connectivity in Connect AI, register the CData MCP Server in Emergent, and interact with live Bitbucket data from Emergent.

Step 1: Configure Bitbucket connectivity for Emergent

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

1. Log into Connect AI, click Sources, and then 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.
   
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 Emergent. 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 Bitbucket connection configured and a PAT generated, Emergent can now connect to Bitbucket data through Connect AI.

Step 2: Configure Connect AI in Emergent

CData Connect AI can be integrated with Emergent in two ways depending on your account tier. Pro and Enterprise users can register the MCP Server directly in the Emergent UI, while free-tier users can describe the integration in natural language and have Emergent's agent build a connected application automatically.

Method 1: Direct MCP Configuration (Pro/Enterprise)

Pro and Enterprise users can register the CData Connect AI MCP Server directly in the Emergent UI. Once registered, agents in any project can call live Bitbucket data through MCP tools without additional setup.

1. Sign in to Emergent and create an account if you do not already have one
2. Click to start a new project. Enter a Project Name and click Create Project
3. In the project chat window, select your preferred model from the dropdown (e.g., Claude 4.5 Sonnet)
4. Click the Advanced Controls icon and then click Select MCP Tools to open the MCP configuration panel
5. In the Select MCPs to use dialog, click + New MCP Server to add a custom MCP server
6. In the Configure New MCP dialog, fill in the following:
   • MCP Name: cdata-mcp
   • Description: (optional) A brief description of the server
   • JSON Configuration: Paste the following, replacing base64-encode-email-pat with your Base64-encoded email:PAT string:

   {
       "mcpServers": {
           "cdata-mcp": {
               "args": [
                   "-y",
                   "mcp-client",
                   "connect",
                   "https://mcp.cloud.cdata.com/mcp"
               ],
               "command": "npx",
               "env": {
                   "MCP_HEADERS": "{\"Authorization\":\"Basic base64-encode-email-pat\"}"
               }
           }
       }
   }
           

   Note: Combine your Connect AI email and PAT in the format email:PAT, then Base64 encode the combined string. For example, given [email protected]:ABC123...XYZ, the value becomes something like: dXNlckBteWRvbWFpbjphSzkvbVB4Mi9Rcjd2TjQ...

   
7. Click Verify and Save to register the MCP server
8. Return to Select MCP Tools and confirm that cdata-mcp is listed and its toggle is enabled. If it is not enabled, toggle it on

With the CData MCP Server registered and enabled, Emergent agents can now query and act on live Bitbucket data through Connect AI in any project.

Query live Bitbucket data from Emergent

With the MCP server configured, start a conversation in the Emergent agent panel to interact with live Bitbucket data.

1. Return to the project chat and enter a prompt to explore your data, for example:
   • List all available catalogs in my cdata-mcp connection.
   • Show the schemas and tables available for Bitbucket.
   • Query the top 5 records from Bitbucket data.
2. The agent calls the CData Connect AI MCP Server and returns live results from Bitbucket data

Method 2: Build an application with natural language (Free)

Free-tier users can direct Emergent to build a full-stack application that connects to the CData Connect AI MCP Server through a natural language prompt. The agent will gather the required endpoint and credentials interactively, then generate a working application wired to live Bitbucket data.

1. Sign in to Emergent and open the chat window
2. Enter a prompt that describes the application you want to build. For example:

   I would like to build a small application that connects to a remote MCP HTTPS server.
   I already have the MCP endpoint URL and the required credentials.
   The application should:
     - Establish a connection to the remote MCP server
     - Authenticate using the provided credentials
     - Retrieve and list all available catalogs from the MCP
   
   Please make sure the credentials are stored securely in a .env file
   and not hardcoded in the application.
           

3. Emergent will prompt you to provide the MCP endpoint URL and authentication credentials. Supply the following values:
   • MCP Endpoint URL: https://mcp.cloud.cdata.com/mcp
   • Authorization: Basic base64(email:PAT)
4. The Emergent agent generates a full-stack application that connects to Bitbucket data through Connect AI and renders live results in the App Preview panel.

At this point, Emergent has built an application that communicates with the CData Connect AI MCP Server and retrieves live Bitbucket data, all from a single natural language prompt.

Get CData Connect AI

To access hundreds of SaaS, Big Data, and NoSQL sources directly from your cloud applications, try CData Connect AI today! Sign up for a free 14-day trial of CData Connect AI, and as always, our world-class Support Team is available to assist you with any questions you may have.