Build Bitbucket-Powered Applications in Claude Code with CData Code Assist MCP

Claude Code is an AI-powered command line tool that enables agentic coding workflows. With support for MCP, Claude Code can connect to local tools and enterprise data sources directly from your terminal, enabling natural language interaction with live systems without switching context.

Model Context Protocol (MCP) is an open standard for connecting LLM clients to external services through structured tool interfaces. MCP servers expose capabilities such as schema discovery and live querying, allowing AI agents to retrieve and reason over real-time data safely and consistently.

The following steps cover installing the CData Code Assist MCP for Bitbucket, configuring the connection to Bitbucket, connecting the Code Assist MCP add-on to Claude Code, and querying live Bitbucket data from within the terminal.

Step 1: Download and install the CData Code Assist MCP for Bitbucket

1. To begin, download the CData Code Assist MCP for Bitbucket 👁 Downloading the CData Code Assist MCP add-on installer
   
2. Find and double-click the installer to begin the installation
3. Run the installer and follow the prompts to complete the installation 👁 Completing the CData Code Assist MCP add-on installation
   

When the installation is complete, you are ready to configure your Code Assist MCP add-on by connecting to Bitbucket.

Step 2: Configure the connection to Bitbucket

1. After installation, open the CData Code Assist MCP for Bitbucket configuration wizard 👁 The CData Code Assist MCP add-on configuration wizard
   

   NOTE: If the wizard does not open automatically, search for "CData Code Assist MCP for Bitbucket" in the Windows search bar and open the application.

   👁 Opening the CData Code Assist MCP add-on configuration wizard (Google Sheets is shown).
   
2. In MCP Configuration > Configuration Name, either select an existing configuration or choose to create a new one 👁 Creating a new configuration
   
3. Name the configuration (e.g. "cdata_bitbucket") and click OK 👁 Naming the configuration
   

4. Enter the appropriate connection properties in the configuration wizard

   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 the Code Assist MCP add-on connection
   
5. Click Connect to authenticate with Bitbucket through OAuth
6. Then, click Save Configuration to save the Code Assist MCP add-on 👁 Saving the Code Assist MCP add-on configuration
   

This process creates a .mcp configuration file that Claude Code will reference when launching the Code Assist MCP add-on. Now with your Code Assist MCP add-on configured, you are ready to connect it to Claude Code.

Step 3: Connect the Code Assist MCP add-on to Claude Code

1. Install the Claude Code CLI using the terminal
2. Open the Claude Code configuration file at ~/.config/claude-code/config.json (or the location shown after initialization)

Option 1: Manually add the MCP configuration

1. Open the mcp.json file in your preferred editor
2. Add the code shown below

{
"mcpServers" : {
 "cdata_bitbucket" : {
 "type" : "stdio",
 "command" : "C:\Program Files\CData\CData Code Assist MCP for Bitbucket\jre\bin\java.exe",
 "args" : [ "-Dfile.encoding=UTF-8", "-jar", "C:\Program Files\CData\CData Code Assist MCP for Bitbucket/lib/cdata.mcp.bitbucket.jar", "cdata_bitbucket" ], 
 "env" : {}
 }
}
}

NOTE: The command value should point to your Java 17+ java.exe executable, and the JAR path should point to the installed CData Code Assist MCP add-on .jar file. The final argument must match the MCP configuration name you saved in the CData configuration wizard (e.g. "cdata_bitbucket").

Option 2: Copy the MCP configuration from the CData Code Assist MCP for Bitbucket UI

1. After saving and testing your connection in the configuration wizard, click Next
👁 Selecting 'Next'

2. Select Claude Code from the AI MCP Tool dropdown
👁 Choosing the required AI MCP tool

3. Click Copy JSON to copy the generated MCP configuration to your clipboard
👁 Copying the MCP configuration

4. Paste the copied JSON into the mcp.json file

Step 4: Verify connection in Claude Code

Claude Code provides tools to verify the connection is active before building.

1. Open a terminal and navigate to your project directory. Run the command claude mcp list
2. Check that your configuration name appears with a Connected status
👁 Checking the connection status

3. Start Claude Code by running claude
4. Inside the Claude Code session, type /mcp to view active servers 👁 Viewing active MCP servers
   

Step 5: Query live Bitbucket data in Claude Code

With the connection verified, you can now use natural language prompts to query and work with live Bitbucket data.

1. Prompt Claude Code to review the instructions for your MCP connection to ensure it has all the appropriate context when writing code 👁 Reviewing MCP connection instructions
   
2. Start building with natural language prompts! For example:

   For my project, data from the Issues is very important. Pull data from the most important columns like Title and ContentRaw.

Claude Code will use the MCP add-on to connect to Bitbucket, retrieve the requested data, and provide results directly in your terminal

Build with Code Assist MCP. Deploy with CData Drivers.

Download Code Assist MCP for free and give your AI tools schema-aware access to live Bitbucket data during development. When you're ready to move to production, CData Bitbucket Drivers deliver the same SQL-based access with enterprise-grade performance, security, and reliability.

Visit the CData Community to share insights, ask questions, and explore what's possible with MCP-powered AI workflows.