Integrate Devin with Live Bitbucket Data Using CData Connect AI

Anusha M B
Anusha M B
Technical Marketing Engineer
Use the CData Connect AI Remote MCP Server to enable Devin, the AI software engineer, to securely access and query live Bitbucket data.

Devin is an AI software engineer from Cognition that plans, writes, and tests code in autonomous sessions. It supports the model context protocol (MCP) through its built-in MCP marketplace, allowing you to install remote MCP servers and give Devin access to external tools and live data sources.

By integrating Devin with CData Connect AI through the built-in MCP Server, Devin gains governed, real-time access to live Bitbucket data. You can list catalogs, explore schemas, and query records from Bitbucket data using natural language prompts, with all data access running securely against authorized sources.

This article explains how to configure Bitbucket connectivity in Connect AI, install the CData Connect AI MCP Server from the Devin MCP marketplace, and verify the integration by querying live Bitbucket data from a Devin session.

Step 1: Configure Bitbucket connectivity for Devin

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

  1. Log into Connect AI, click Sources, and then click Add Connection
  2. Adding a connection in Connect AI
  3. Select Bitbucket from the Add Connection panel
  4. Selecting data source
  5. 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.
    Configuring a connection (Salesforce is shown)
  6. Click Save & Test
  7. Navigate to the Permissions tab and update user-based permissions
  8. Updating permissions

With the Bitbucket connection configured, Devin can now connect to Bitbucket data through Connect AI.

Step 2: Install the Connect AI MCP Server in Devin

Next, install the CData Connect AI MCP Server from the Devin MCP servers list so your sessions can discover and call live data tools through Connect AI.

Note: Installing MCP servers in Devin requires the Manage MCP Servers permission. If you don't have this permission, use the Suggest option or contact your organization admin.

  1. Log into Devin and navigate to Settings and Connections, then select the MCP servers tab
  2. Search for CData Connect AI in the marketplace and select the verified listing
  3. Viewing MCP servers in Devin and searching for CData Connect AI
  4. Click Install and enable. When prompted, complete the OAuth flow to authenticate with your Connect AI account Installing the Connect AI MCP Server in Devin
  5. Once installed, confirm the Enable in sessions toggle is on and click Test tools. Devin validates the connection and lists the available Connect AI tools, such as getCatalogs, getSchemas, getTables, and queryData Verifying the Connect AI MCP tools in Devin

With the MCP server installed and enabled, the Connect AI tools are available to every Devin session in your workspace.

Step 3: Query live Bitbucket data from Devin

With the integration complete, start a Devin session and interact with live Bitbucket data through natural language prompts.

  1. From the Devin home page, start a new session
  2. In the session prompt, ask Devin to work with your Connect AI data, for example:
    • Can you list the connections in CData Connect AI
    • Show the available schemas and tables for Bitbucket
    • Query the top 5 records from a table in Bitbucket
  3. Devin calls the Connect AI MCP Server and returns live results from Bitbucket data directly in the session. You can follow the tool calls, inputs, and outputs in the Progress panel Querying live data from a Devin session

At this point, Devin communicates with the Connect AI MCP Server and retrieves live Bitbucket data through remote MCP tools directly from your sessions, whether you're exploring data, building features against it, or automating engineering tasks.

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