Build Azure Data Lake Storage-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 Azure Data Lake Storage, configuring the connection to Azure Data Lake Storage, connecting the Code Assist MCP add-on to Claude Code, and querying live Azure Data Lake Storage data from within the terminal.
Step 1: Download and install the CData Code Assist MCP for Azure Data Lake Storage
- To begin, download the CData Code Assist MCP for Azure Data Lake Storage
- Find and double-click the installer to begin the installation
- Run the installer and follow the prompts to complete the installation
When the installation is complete, you are ready to configure your Code Assist MCP add-on by connecting to Azure Data Lake Storage.
Step 2: Configure the connection to Azure Data Lake Storage
- After installation, open the CData Code Assist MCP for Azure Data Lake Storage configuration wizard
NOTE: If the wizard does not open automatically, search for "CData Code Assist MCP for Azure Data Lake Storage" in the Windows search bar and open the application.
- In MCP Configuration > Configuration Name, either select an existing configuration or choose
to create a new one
- Name the configuration (e.g. "cdata_adls") and click OK
-
Enter the appropriate connection properties in the configuration wizard
Authenticating to a Gen 1 DataLakeStore Account
Gen 1 uses OAuth 2.0 in Entra ID (formerly Azure AD) for authentication.
For this, an Active Directory web application is required. You can create one as follows:
To authenticate against a Gen 1 DataLakeStore account, the following properties are required:
- Schema: Set this to ADLSGen1.
- Account: Set this to the name of the account.
- OAuthClientId: Set this to the application Id of the app you created.
- OAuthClientSecret: Set this to the key generated for the app you created.
- TenantId: Set this to the tenant Id. See the property for more information on how to acquire this.
- Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.
Authenticating to a Gen 2 DataLakeStore Account
To authenticate against a Gen 2 DataLakeStore account, the following properties are required:
- Schema: Set this to ADLSGen2.
- Account: Set this to the name of the account.
- FileSystem: Set this to the file system which will be used for this account.
- AccessKey: Set this to the access key which will be used to authenticate the calls to the API. See the property for more information on how to acquire this.
- Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.
- Click Connect to authenticate with Azure Data Lake Storage through OAuth
- Then, click Save Configuration to save the Code Assist MCP add-on
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
- Install the Claude Code CLI using the terminal
- 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
- Open the mcp.json file in your preferred editor
- Add the code shown below
{
"mcpServers" : {
"cdata_adls" : {
"type" : "stdio",
"command" : "C:\Program Files\CData\CData Code Assist MCP for Azure Data Lake Storage\jre\bin\java.exe",
"args" : [ "-Dfile.encoding=UTF-8", "-jar", "C:\Program Files\CData\CData Code Assist MCP for Azure Data Lake Storage/lib/cdata.mcp.adls.jar", "cdata_adls" ],
"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_adls").
Option 2: Copy the MCP configuration from the CData Code Assist MCP for Azure Data Lake Storage UI
- After saving and testing your connection in the configuration wizard, click Next
- Select Claude Code from the AI MCP Tool dropdown
- Click Copy JSON to copy the generated MCP configuration to your clipboard
- 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.
- Open a terminal and navigate to your project directory. Run the command claude mcp list
- Check that your configuration name appears with a Connected status
- Start Claude Code by running claude
- Inside the Claude Code session, type /mcp to view active servers
Step 5: Query live Azure Data Lake Storage data in Claude Code
With the connection verified, you can now use natural language prompts to query and work with live Azure Data Lake Storage data.
- Prompt Claude Code to review the instructions for your MCP connection to ensure it has all the appropriate context when writing code
- Start building with natural language prompts! For example:
For my project, data from the Resources is very important. Pull data from the most important columns like FullPath and Permission.
Claude Code will use the MCP add-on to connect to Azure Data Lake Storage, 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 Azure Data Lake Storage data during development. When you're ready to move to production, CData Azure Data Lake Storage 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.