databricks-ai-dev-kit

Databricks AI Dev Kit

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📣 A big step forward: AI Dev Kit skills are now official Databricks AI Tools

The skills from this AI Dev Kit repository are now delivered as part of Databricks AI Tools, a Databricks engineering-owned repository, built and maintained in close collaboration with field engineering.

Databricks AI Tools are installed and kept up to date directly through the Databricks CLI (databricks aitools install), or through the AI Dev Kit installer, which delegates to the CLI and still guides you through the process.

AI Tools work with any agent and include a first-class Genie One integration.

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Already installed? Re-run the Quick Start (install) in this repo to uninstall older skills and the MCP server before installing the official AI Tools — see Where Skills Come From.

What stays: The MCP server and Builder App remain in this repository. The Builder App will keep being developed and improved, and the MCP server will be maintained and updated on a best-effort basis as GitHub issues are filed.

What's next: AI Dev Kit will continue to guide you through setting up your AI coding environment and be a place to find experimental tools developed by Field Engineering. We're working on several tutorials to help you get started using coding agents for building on Databricks — including getting started with Genie Code and Omnigent — which will land in a future update. The bundled skill files in this repo are deprecated and kept for reference only.

A few skills were renamed or merged in the official install. Most names are unchanged; the exceptions are:

Previously (AI Dev Kit)	Official Databricks skills
databricks-bundles	databricks-dabs
databricks-genie	databricks-genie-agents
databricks-spark-declarative-pipelines	databricks-pipelines
databricks-lakebase-autoscale, databricks-lakebase-provisioned	databricks-lakebase (merged)
databricks-config	databricks-core (merged)

🔒 Proactive Dependency Security
As part of our commitment to supply chain integrity, we continually monitor our dependency tree against known vulnerabilities and industry advisories. In response to a recently disclosed supply chain incident affecting litellm versions 1.82.7–1.82.8, we have audited our packages and removed the litellm dependency for most usage. It is solely used in the test directory for skills evaluation and optimization, and has been pinned to a safe version.
For full third-party attribution, see NOTICE.txt.

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Install or Upgrade

Options	Best For	Start Here
:star: Install Skills	Start here! Follow quick install instructions to add Databricks skills for your user or existing project folder	Quick Start (install)
Genie Code Skills	Upload selected skills into your workspace for Genie Code. Note: much of the content in the public Databricks skills is already included in Genie Code.	Genie Code skills (install)
Visual Builder App	Web-based UI for Databricks development	databricks-builder-app/
MCP Tools	Standalone MCP server exposing Databricks actions to AI clients. Note: We recommend skills instead, but maintain this as a good foundation if a custom MCP server is required.	Register MCP server

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AI-Assisted Development on Databricks

Databricks offers two paths for AI-assisted coding. Choose the one that matches your environment.

Free, first-party AI coding inside Databricks

Built into every Databricks workspace with deep native product context — your notebooks, jobs, and Unity Catalog data are already in scope. Ideal for users who have not started using AI-driven development tools or that are comfortable in Databricks workspace.

Databricks expertise, in the editor you already use

Curated by Databricks field experts. Brings tutorials, patterns, and the official Databricks agent skills to your AI coding tools to build on Databricks — wherever you're already coding.

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What Can I Build?

• Spark Declarative Pipelines (streaming tables, CDC, SCD Type 2, Auto Loader)
• Databricks Jobs (scheduled workflows, multi-task DAGs)
• AI/BI Dashboards (visualizations, KPIs, analytics)
• Unity Catalog (tables, volumes, governance)
• Genie Spaces (natural language data exploration)
• Knowledge Assistants (RAG-based document Q&A)
• MLflow Experiments (evaluation, scoring, traces)
• Model Serving (deploy ML models and AI agents to endpoints)
• Databricks Apps (full-stack web applications with foundation model integration)
• ...and more

Building a Databricks App? The databricks-apps-python skill defaults to AppKit (TypeScript + React) — the recommended path for most Apps use cases — and falls back to the Python frameworks (Dash, Streamlit, Flask, FastAPI, Gradio, Reflex) when you need a specific one. If you specifically need the APX (FastAPI + React) framework, that skill now lives in the databricks-solutions/apx repo.

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Quick Start

Prerequisites

• Databricks CLI v1.0.0+ - Command line interface for Databricks (v1.0.0+ ships databricks aitools, which installs most skills)
• AI coding environment (one or more):
  • Claude Code
  • Cursor
  • Gemini CLI
  • Antigravity
  • Codex
  • Copilot
  • Windsurf
  • OpenCode
  • Kiro

Install in existing project

By default this will install at a project level rather than a user level. This is often a good fit, but requires you to run your client from the exact directory that was used for the install. You can install for your user across all projects on the machine by passing --global or setting the scope to global in the interactive install. Note: Project configuration files can be found under these folder: .claude, .cursor, .gemini, .codex, .github, .agents, .windsurf, .codeium, .opencode, .kiro, or opencode.json

Mac / Linux

Basic installation (uses DEFAULT profile, project scope)

bash <(curl -sL https://raw.githubusercontent.com/databricks-solutions/ai-dev-kit/main/install.sh)

Global installation with force reinstall

bash <(curl -sL https://raw.githubusercontent.com/databricks-solutions/ai-dev-kit/main/install.sh) --global --force

Install specific skills only

bash <(curl -sL https://raw.githubusercontent.com/databricks-solutions/ai-dev-kit/main/install.sh) --skills databricks-core,databricks-bundles,databricks-pipelines

Next steps: Respond to interactive prompts and follow the on-screen instructions.

• Note: Cursor and Copilot require updating settings manually after install.

Windows (PowerShell)

Basic installation (uses DEFAULT profile, project scope)

irm https://raw.githubusercontent.com/databricks-solutions/ai-dev-kit/main/install.ps1 | iex

Download script first

irm https://raw.githubusercontent.com/databricks-solutions/ai-dev-kit/main/install.ps1 -OutFile install.ps1

Global installation with force reinstall

.\install.ps1 -Global -Force

Install for specific tools only

.\install.ps1 -Tools cursor,gemini,antigravity

Next steps: Respond to interactive prompts and follow the on-screen instructions.

• Note: Cursor and Copilot require updating settings manually after install.

Where Skills Come From

Most skills are delivered as Databricks AI Tools through the Databricks CLI. The installer assembles them from two upstream sources — nothing is bundled in this repo anymore:

Source	Skills	Mechanism
databricks/databricks-agent-skills	Most Databricks skills (jobs, pipelines, DABs, SQL, Unity Catalog, apps, Genie, …)	Delegated to databricks aitools install — requires Databricks CLI v1.0.0+
mlflow/skills	MLflow skills	Fetched from main (override with MLFLOW_REF)

Skills installed via databricks aitools are managed by the CLI afterwards — update them with databricks aitools update and remove them with databricks aitools uninstall. For tools the CLI can't target yet (Gemini CLI, Windsurf, Kiro), the installer installs the same skills into each tool's skills directory.

Use --list-skills to see every skill and profile, and --dry-run to preview exactly what an install would do (resolved refs and the aitools command) without changing anything. Some skills were renamed or consolidated in the move — see Breaking change: skill sources and names below.

Variable	Default	Purpose
MLFLOW_REF	main	Ref for the MLflow skills fetch (the repo is tagless)
INCLUDE_PRERELEASES	0	Set to 1 to allow -rc/-beta tags when resolving latest
DRY_RUN	false	Set to 1 to print the install plan and exit

The installer also records what it installed (resolved refs, commit SHAs, aitools release) in skills.lock inside the scope-local .ai-dev-kit/ state directory.

Update