How to Query Live Bitbucket Data in Claude Desktop

Model Context Protocol (MCP) is an emerging, open-source standard for connecting LLMs with external services and data sources. Through MCP Servers, AI clients can perform actions like opening Jira tickets, posting Slack messages, committing GitHub branches and more. With CData MCP Servers, these capabilities expand exponentially.

In this article, we guide the reader through installing the CData MCP Server for Bitbucket, configuring the connection to Bitbucket, and asking questions of the data in Claude Desktop.

Prerequisites

You need to download Claude Desktop (download) and create an account before continuing.

Overview

Here's a quick overview of the steps:

1. Download and install the CData MCP Server for Bitbucket
2. Configure the connection to Bitbucket
3. Ask questions about the data in Claude Desktop

Step 1: Download and install the CData MCP Server

1. To begin, navigate to https://www.cdata.com/solutions/mcp/connectors and download the CData MCP Server for Bitbucket.
2. Find and double-click the installer to begin the installation.
3. Follow the prompts to complete the installation.

When the installation is complete, you are ready to configure your MCP Server by connecting to Bitbucket.

Step 2: Configure the connection to Bitbucket

1. After installation, the CData MCP Server configuration wizard should open automatically.

   NOTE: If the wizard does not open automatically, search for "CData MCP Server" in the Windows search bar and double-click the application.

2. Click the dropdown menu in MCP Configuration > Configuration Name and select ""
3. Name the configuration (e.g. "cdatabitbucket") and click "OK."

   NOTE: This name is used as the name for the MCP server and as the prefix for all of the MCP Server's tools.

   

4. Connecting 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.

   Enter the appropriate connection properties in the configuration wizard.

   
5. Click "Connect" to authenticate with Bitbucket through OAuth.

   NOTE: The configuration wizard should open your browser and ask you to sign into Google. If your browser does not open, close the configuration wizard and re-open the application using "Run as Administrator" (see below).

   
6. Finally, click "Save Configuration" to save the MCP server.

   NOTE: This saves the configuration details to a separate file and updates the Claude Desktop configuration file (claude_desktop_config.json) to start the CData MCP Server when the Claude Desktop client starts.

With the CData MCP Server configured, you are ready to start asking questions of your live data from Claude.

Step 3: Ask AI for answers from live Bitbucket data

Now that we have installed the CData MCP Server and configured a connection, we are ready to start with Bitbucket data in Claude Desktop.

1. Open Claude Desktop. It may take a moment for the MCP Servers to start, but you will see the list of servers and tools available in the Claude interface (look for the settings icon below the prompt bar).

   You can individually enable and disable specific tools by clicking on the server name.

2. Now that you have connected, you can ask Claude questions about the Bitbucket data. For example: "Can you give me a quantitative analysis about my closed-won opportunities by industry?"

   NOTE: Claude may need to explore the Bitbucket data to make sense of it before it can begin answering questions of the data. The tabular model presented by CData alongside the database tools available simplify the data exploration and analysis for an LLM.

   

Connect your AI to your data today!

CData MCP Servers make it easier than ever for LLMs to work with live enterprise data. To explore the technology hands-on, download a free MCP Server or visit the CData Community to share insights, ask questions, and help shape the future of enterprise-ready AI.