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By leary-poken
Databricks development toolkit with skills for data engineering, ML, and AI agents plus MCP tools for direct Databricks operations
npx claudepluginhub leary-poken/ai-dev-kit --plugin databricks-ai-dev-kitA brief one-sentence description of what this skill helps with.
Create and manage Databricks Agent Bricks: Knowledge Assistants (KA) for document Q&A, Genie Spaces for SQL exploration, and Supervisor Agents (MAS) for multi-agent orchestration. Use when building conversational AI applications on Databricks.
Use Databricks built-in AI Functions (ai_classify, ai_extract, ai_summarize, ai_mask, ai_translate, ai_fix_grammar, ai_gen, ai_analyze_sentiment, ai_similarity, ai_parse_document, ai_query, ai_forecast) to add AI capabilities directly to SQL and PySpark pipelines without managing model endpoints. Also covers document parsing and building custom RAG pipelines (parse → chunk → index → query).
Create Databricks AI/BI dashboards. CRITICAL: You MUST test ALL SQL queries via execute_sql BEFORE deploying. Follow guidelines strictly.
Builds Python-based Databricks applications using Dash, Streamlit, Gradio, Flask, FastAPI, or Reflex. Handles OAuth authorization (app and user auth), app resources, SQL warehouse and Lakebase connectivity, model serving integration, and deployment. Use when building Python web apps, dashboards, ML demos, or REST APIs for Databricks, or when the user mentions Streamlit, Dash, Gradio, Flask, FastAPI, Reflex, or Databricks app.
Admin access level
Server config contains admin-level keywords
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Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Databricks development toolkit with skills for data engineering, ML, and AI agents plus MCP tools for direct Databricks operations
Claude Code skill pack for Databricks (24 skills)
Databricks skills for CLI, Apps, Unity Catalog, Model Serving, Declarative Automation Bundles (DABs), and more.
Editorial "Data Engineering" bundle for Claude Code from Antigravity Awesome Skills.
This plugin provides a specialized suite of skills for data engineers and database practitioners working on Google Cloud. It acts as an expert assistant, allowing you to use natural language prompts in your preferred coding agent to architect complex data pipelines, transform data with dbt, write Spark and BigQuery SQL notebooks, and orchestrate end-to-end workflows across GCP's data ecosystem.
Data engineering plugin - warehouse exploration, pipeline authoring, Airflow integration
AI-Driven Development (vibe coding) on Databricks just got a whole lot better. The AI Dev Kit gives your AI coding assistant (Claude Code, Cursor, Windsurf, etc.) the trusted sources it needs to build faster and smarter on Databricks.
| Adventure | Best For | Start Here |
|---|---|---|
| :star: Install AI Dev Kit | Start here! Follow quick install instructions to add to your existing project folder | Quick Start (install) |
| Visual Builder App | Web-based UI for Databricks development | databricks-builder-app/ |
| Core Library | Building custom integrations (LangChain, OpenAI, etc.) | pip install |
| Skills Only | Provide Databricks patterns and best practices (without MCP functions) | Install skills |
| MCP Tools Only | Just executable actions (no guidance) | Register MCP server |
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. Note: Project configuration files can be re-used in other projects. You find these configs under .claude, .cursor, or .gemini
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
Specify profile and force reinstall
bash <(curl -sL https://raw.githubusercontent.com/databricks-solutions/ai-dev-kit/main/install.sh) --profile DEFAULT --force
Install for specific tools only
bash <(curl -sL https://raw.githubusercontent.com/databricks-solutions/ai-dev-kit/main/install.sh) --tools cursor,gemini
Next steps: Respond to interactive prompts and follow the on-screen instructions.
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
Specify profile and force reinstall
.\install.ps1 -Profile DEFAULT -Force
Install for specific tools only
.\install.ps1 -Tools cursor,gemini
Next steps: Respond to interactive prompts and follow the on-screen instructions.
Full-stack web application with chat UI for Databricks development:
cd ai-dev-kit/databricks-builder-app
./scripts/setup.sh
# Follow instructions to start the app
Use databricks-tools-core directly in your Python projects:
from databricks_tools_core.sql import execute_sql