iflow-mcp_vivian-xie-db-genie_mcp_server

# Genie MCP Server This project provides an async server for interacting with Databricks Genie via a MCP StreamableHTTP Protocol. It enables users to query Genie and receive answers or data, leveraging Databricks authentication and robust error handling. ## Features - Async API server using Starlette and Uvicorn - Integration with Databricks Genie for conversational queries - Automatic OAuth token management for Databricks ## Project Structure - `mcp_server.py`: Main server entry point, exposes the tool via MCP StreamableHTTP Protocol. - `genie_room.py`: Handles Genie API interactions and conversation logic. - `token_minter.py`: Manages Databricks OAuth token minting and refreshing. - `requirements.txt`: Python dependencies. - `app.yaml`: Example deployment configuration. ## Deploying to Databricks Apps You can deploy the Genie MCP Server as a Databricks app by following these steps: 1. **Clone the Repository to Your Workspace** In your Databricks workspace, navigate to the directory where you want to deploy the app (e.g., `/Workspace/Users/your.email@databricks.com/genie_mcp_server`). Then, clone the repository: ```bash git clone https://github.com/your-org/genie_mcp_server.git ``` 2. **Configure the Genie Space ID and Other Environment Variables** Open the `app.yaml` file in the root of the cloned repository. Update the `SPACE_ID` value to match your Genie space. Example `app.yaml`: ```yaml command: - "python" - "mcp_server.py" env: - name: "SPACE_ID" value: "your_space_id" ``` 3. **Create and Deploy the App in Databricks** - Go to the Databricks Apps interface. - Create a new app and specify the path to the directory where you cloned the repository. - Complete the app creation and deployment process. ```databricks apps deploy genie-mcp-server --source-code-path /Workspace/Users/your.email@databricks.com/genie_mcp_server``` 4. **Access the API** Once deployed, your Genie MCP Server app…