Use ChatGPT to Talk to Your Bitbucket Data via CData Connect AI

ChatGPT is an AI chatbot developed by OpenAI, launched in November 2022. Based on large language models (LLMs), it enables users to refine and steer conversations through natural language processing. ChatGPT's developer mode, available to Plus and Pro subscribers, provides full Model Context Protocol (MCP) support for connecting to external data sources and tools.

CData Connect AI offers a dedicated cloud-to-cloud interface for connecting to Bitbucket data. The CData Connect AI Remote MCP Server enables secure communication between ChatGPT and Bitbucket. This allows you to ask questions and take actions on your Bitbucket data using ChatGPT, all without the need for data replication to a natively supported database. With its inherent optimized data processing capabilities, CData Connect AI efficiently channels all supported SQL operations, including filters and JOINs, directly to Bitbucket. This leverages server-side processing to swiftly deliver the requested Bitbucket data.

Step 1: Configure Bitbucket Connectivity for ChatGPT

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

1. Log into your Connect AI account, 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

With the connection configured, we are ready to connect to Bitbucket data from ChatGPT.

Step 2: Connect ChatGPT to CData Connect AI

Follow these steps to add a CData Connect AI connection in ChatGPT:

1. Sign in to ChatGPT with a Plus or Pro subscription.
2. Navigate to Apps from the left panel.
3. Select the CData Connect AI app from the list.
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4. Click Connect to authenticate to your Connect AI account.

5. Click Sign in with CData Connect AI to add Connect AI to your ChatGPT account.

6. After successful authorization, you will be redirected back to ChatGPT.
7. Click Start Chat to start a new conversation in ChatGPT with Connect AI connected at the background.

Step 3: Explore Live Bitbucket Data with ChatGPT

1. Start a new conversation in ChatGPT.
2. Connect AI should ideally be automatically enabled in the chat. If not, navigate to -> More -> CData Connect AI, under the chatbox, to enable the connector from the dropdown

3. You can now start exploring your data with natural language prompts. ChatGPT will use the Connect AI MCP server to query your live Bitbucket data. Example prompts:
   • "Show me all customers from the last 30 days"
   • "What are my top performing products?"
   • "Analyze sales trends for this quarter"
   • "List all active projects and their current status"
   Refer to CData prompt library for more prompt ideas.

4. Permit ChatGPT to access your Bitbucket data. Click Query Data to continue, or Deny to refuse.

5. ChatGPT translates your natural language queries into SQL and execute them against your Bitbucket data through the Connect AI MCP server.

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