How to Access Live Lakebase Data in Visual Studio Code via Cline
Cline is an autonomous coding agent right in your IDE, capable of creating/editing files, running commands, using the browser, and more with your permission every step of the way. When paired with the CData MCP Server for Lakebase, you get live access to CRM data within your IDE, enabling you to build, test, and validate data-driven features using real-time schema and records without ever leaving your development environment.
This article outlines how to run the CData MCP Server for Lakebase on WSL (Windows Subsystem for Linux) and connect to it from the Cline extension in Visual Studio Code on Windows.
Background
CData MCP Servers are typically designed for clients like Claude Desktop. However, when attempting to use the server via the Cline extension in Windows VS Code, the following error occurred:
MCP error -32000: Connection closed
This issue is suspected to be caused by I/O handling problems in the stdio transport implementation on the Windows version of the Cline extension.
- Related GitHub Issue: https://github.com/cline/cline/issues/3464
- Additionally, environment variables such as PATH may not be inherited correctly when launching processes like Java or Node.
Prerequisites
- Visual Studio Code installed on Windows
- Cline extension installed and configured in VS Code
- Windows Subsystem for Linux (WSL) installed with a working Linux distribution (e.g., Ubuntu)
- Java 21+ JRE installed in WSL
- CData MCP Server for Lakebase installed on Windows
Step 1: Authenticate with Lakebase (on Windows)
Before running the MCP Server in WSL, you must complete authentication flow in a Windows environment. This ensures all necessary credentials are generated and stored properly. Find and run the "CData MCP Server for Lakebase" or execute the MCP Server JAR file to open the configuration wizard.
java -jar "C:\Program Files\CData\CData MCP Server for Lakebase 2024\lib\cdata.mcp.lakebase.jar"
Connecting to Lakebase
To connect to Databricks Lakebase, start by setting the following properties:- DatabricksInstance: The Databricks instance or server hostname, provided in the format instance-abcdef12-3456-7890-abcd-abcdef123456.database.cloud.databricks.com.
- Server: The host name or IP address of the server hosting the Lakebase database.
- Port (optional): The port of the server hosting the Lakebase database, set to 5432 by default.
- Database (optional): The database to connect to after authenticating to the Lakebase Server, set to the authenticating user's default database by default.
OAuth Client Authentication
To authenicate using OAuth client credentials, you need to configure an OAuth client in your service principal. In short, you need to do the following:
- Create and configure a new service principal
- Assign permissions to the service principal
- Create an OAuth secret for the service principal
For more information, refer to the Setting Up OAuthClient Authentication section in the Help documentation.
OAuth PKCE Authentication
To authenticate using the OAuth code type with PKCE (Proof Key for Code Exchange), set the following properties:
- AuthScheme: OAuthPKCE.
- User: The authenticating user's user ID.
For more information, refer to the Help documentation.
Configuring the CData MCP Server
Name your MCP Server (e.g. cdatalakebase), enter the required connection properties, and click "Connect."
Upon successful connection, the following directory and files will be created:
C:\Users\<username>\AppData\Roaming\CData\lakebase Provider\ |-- cdatalakebase.mcp |-- (other supporting config files)
Step 2: Copy the MCP Server Configuration into WSL
Next, copy the entire configuration folder from Windows into your WSL environment.
mkdir -p ~/.config/CData/ cp -r /mnt/c/Users/<username>/AppData/Roaming/CData/"lakebase Provider" ~/.config/CData/
Ensure the destination path matches exactly: ~/.config/CData/lakebase Provider/.
Step 3: Install the MCP Server on WSL
Install Java and place the MCP Server JAR in the desired location within WSL:
sudo apt update sudo apt install openjdk-21-jre-headless sudo mkdir -p /opt/cdata/mcp_lakebase/lib sudo cp /mnt/c/Program\ Files/CData/CData\ MCP\ Server\ for\ Lakebase\ 2024/lib/cdata.mcp.lakebase.jar /opt/cdata/mcp_lakebase/lib/
Step 4: Configure Cline
Now, configure the Cline extension to launch the MCP Server inside WSL using the wsl command.
Create or update cline_mcp_settings.json with the following content:
{
"mcpServers": {
"cdatalakebase": {
"autoApprove": ["*"],
"disabled": false,
"timeout": 60,
"type": "stdio",
"command": "wsl",
"args": [
"-d",
"Ubuntu", // Replace with your installed WSL distro name
"--",
"/usr/bin/java",
"-jar",
"/opt/cdata/mcp_lakebase/lib/cdata.mcp.lakebase.jar",
"cdatalakebase"
],
"env": {
"JAVA_TOOL_OPTIONS": "-Xmx2g"
}
}
}
}
Note: Replace Ubuntu with your actual WSL distribution name (e.g., Ubuntu-22.04). Run wsl -l in PowerShell or CMD to confirm.
Step 5: Interact with Live Data in Cline
From within Visual Studio Code, you can now run MCP commands through the Cline extension.
cdatalakebase_get_tables cdatalakebase_get_columns Orders
If configured correctly, these commands will return a list of available Lakebase objects and metadata, allowing you to interact with your CRM schema in real time.
Try natural language prompts like:
- "Generate a React form to create a new Lakebase Lead."
- "Write a Python function to pull Opportunities closed this quarter."
Connect your AI to your data today!
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