databricks-genie

name	databricks-genie
description	Create and query Databricks Genie Spaces for natural language SQL exploration. Use when building Genie Spaces, exporting and importing Genie Spaces, migrating Genie Spaces between workspaces or environments, or asking questions via the Genie Conversation API.

Databricks Genie

Create, manage, and query Databricks Genie Spaces - natural language interfaces for SQL-based data exploration.

Overview

Genie Spaces allow users to ask natural language questions about structured data in Unity Catalog. The system translates questions into SQL queries, executes them on a SQL warehouse, and presents results conversationally.

When to Use This Skill

Use this skill when:

• Creating a new Genie Space for data exploration
• Adding sample questions to guide users
• Connecting Unity Catalog tables to a conversational interface
• Asking questions to a Genie Space programmatically (Conversation API)
• Exporting a Genie Space configuration (serialized_space) for backup or migration
• Importing / cloning a Genie Space from a serialized payload
• Migrating a Genie Space between workspaces or environments (dev → staging → prod)
  • Only supports catalog remapping where catalog names differ across environments
  • Not supported for schema and/or table names that differ across environments
  • Not including migration of tables between environments (only migration of Genie Spaces)

MCP Tools

Space Management

Tool	Purpose
create_or_update_genie	Create or update a Genie Space (supports serialized_space)
get_genie	Get space details (by ID and support include_serialized_space parameter) or list all spaces (no ID)
delete_genie	Delete a Genie Space
migrate_genie	Export (type="export") or import (type="import") a Genie Space for cloning / migration

Conversation API

Tool	Purpose
ask_genie	Ask a question or follow-up (conversation_id optional)

Supporting Tools

Tool	Purpose
get_table_details	Inspect table schemas before creating a space
execute_sql	Test SQL queries directly

Quick Start

1. Inspect Your Tables

Before creating a Genie Space, understand your data:

get_table_details(
    catalog="my_catalog",
    schema="sales",
    table_stat_level="SIMPLE"
)

2. Create the Genie Space

create_or_update_genie(
    display_name="Sales Analytics",
    table_identifiers=[
        "my_catalog.sales.customers",
        "my_catalog.sales.orders"
    ],
    description="Explore sales data with natural language",
    sample_questions=[
        "What were total sales last month?",
        "Who are our top 10 customers?"
    ]
)

3. Ask Questions (Conversation API)

ask_genie(
    space_id="your_space_id",
    question="What were total sales last month?"
)
# Returns: SQL, columns, data, row_count

4. Export & Import (Clone / Migrate)

Export a space (preserves all tables, instructions, SQL examples, and layout):

exported = migrate_genie(type="export", space_id="your_space_id")
# exported["serialized_space"] contains the full config

Clone to a new space (same catalog):

migrate_genie(
    type="import",
    warehouse_id=exported["warehouse_id"],
    serialized_space=exported["serialized_space"],
    title=exported["title"],  # override title; omit to keep original
    description=exported["description"],
)

Cross-workspace migration: Each MCP server is workspace-scoped. Configure one server entry per workspace profile in your IDE's MCP config, then migrate_genie(type="export") from the source server and migrate_genie(type="import") via the target server. See spaces.md §Migration for the full workflow.

Reference Files

• spaces.md - Creating and managing Genie Spaces
• conversation.md - Asking questions via the Conversation API

Prerequisites

Before creating a Genie Space:

1. Tables in Unity Catalog - Bronze/silver/gold tables with the data
2. SQL Warehouse - A warehouse to execute queries (auto-detected if not specified)

Creating Tables

Use these skills in sequence:

1. databricks-synthetic-data-gen - Generate raw parquet files
2. databricks-spark-declarative-pipelines - Create bronze/silver/gold tables

Common Issues

See spaces.md §Troubleshooting for a full list of issues and solutions.

Related Skills

• databricks-agent-bricks - Use Genie Spaces as agents inside Supervisor Agents
• databricks-synthetic-data-gen - Generate raw parquet data to populate tables for Genie
• databricks-spark-declarative-pipelines - Build bronze/silver/gold tables consumed by Genie Spaces
• databricks-unity-catalog - Manage the catalogs, schemas, and tables Genie queries