This project implements a Model Context Protocol (MCP) server that exposes Databricks Genie API capabilities as tools
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"databricks-genie-mcp": {
"command": "<see-readme>",
"args": []
}
}
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This project implements a Model Context Protocol (MCP) server that exposes Databricks Genie API capabilities as tools. It allows you to integrate Databricks' no-code AI/BI assistant features with other applications through a standardized interface, enabling powerful natural language querying of your Databricks data.
No automated test available for this server. Check the GitHub README for setup instructions.
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This project implements a Model Context Protocol (MCP) server that exposes Databricks Genie API capabilities as tools. It allows you to integrate Databricks' no-code AI/BI assistant features with other applications through a standardized interface, enabling powerful natural language querying of your Databricks data.
For a detailed explanation and example use cases, please see the accompanying blog post.
Clone the Repository (if you haven't already)
# Add clone command if needed
Navigate to the Server Directory
cd genie_api
Install Dependencies
pip install -r requirements.txt
Configure Authentication
Set the required environment variables for the Databricks SDK to connect to your workspace. Create a .env file in this directory (genie_api/) or set them globally:
# --- .env file content ---
# For PAT authentication (recommended for development)
# DATABRICKS_HOST=https://your-workspace.cloud.databricks.com
# DATABRICKS_TOKEN=your-personal-access-token
# Or for OAuth with service principal (recommended for production)
DATABRICKS_HOST=https://your-workspace.cloud.databricks.com
DATABRICKS_CLIENT_ID=your-client-id
DATABRICKS_CLIENT_SECRET=your-client-secret
# --- end .env file content ---
Ensure the .env file is added to your `.gitignore!
Run the Server Locally
python server.py
The server will start and listen for connections via standard input/output (stdio).
This MCP server is designed to be used with MCP clients like Claude Desktop. Follow these steps to connect:
Install Claude Desktop: Download and install from the official website.
Configure Claude Desktop:
mcpServers object in the claude_desktop_config.json file, adjusting paths as needed:{
"mcpServers": {
"databricks-genie": {
"command": "python", // Or python3, or the full path to your python executable
"args": [
"/full/absolute/path/to/your/project/genie_api/server.py"
],
"workingDirectory": "/full/absolute/path/to/your/project/genie_api/"
}
// ... potentially other servers ...
}
}
server.py and the genie_api directory.command is accessible by Claude Desktop.workingDirectory ensures the server can find auth.py and your .env file.Restart Claude Desktop: Close and reopen the application.
Verify: Click the hammer icon (Tools) in the chat input. You should see the databricks-genie tools listed (e.g., start_conversation, create_message).
Now you can ask Claude questions like "What was our DBU consumption last month?" or "Who accessed the PII table yesterday?", and it will use the tools pro