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andregit2026
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databricks-testing

Test Databricks Python and SQL code against real clusters via MCP.

Updated Aug 23, 2026
Search Tags:#testing#debugging#mcp#sql#pyspark#databricks
One-click install
npx skills add https://github.com/andregit2026/Databricks_DQ_Business --skill databricks-testing
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: databricks-testing
Source: https://github.com/andregit2026/Databricks_DQ_Business/tree/main/.claude/skills/databricks-general-skill-testing
Command: npx skills add https://github.com/andregit2026/Databricks_DQ_Business --skill databricks-testing

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill enables rapid testing and iteration of Databricks code against real clusters using the MCP Command Execution API, reducing debugging cycles.

Core Features & Use Cases

  • Stateless Testing: Run single commands on a live cluster without preserving state between calls.
  • Stateful Debugging: Create a persistent Python/SQL context to iteratively build and verify transformations.
  • End-to-End Validation: Validate notebooks, pipelines, and SQL queries against production-like data while capturing complete outputs.

Quick Start

Start by choosing a stateless test for a single command, or create a context for an iterative, stateful session on your Databricks cluster.

Frequently Asked Questions about databricks-testing

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I test PySpark and SQL code against a real Databricks cluster?▼

You can test PySpark and SQL code against a real Databricks cluster by using the MCP Command Execution API to run stateless single commands or stateful sessions for iterative validation.

What is the best way to debug Databricks transformations iteratively?▼

Debugging Databricks transformations iteratively requires creating a persistent context using create_context, executing commands with execute_command_with_context, and destroying it with destroy_context to maintain state between calls.

Can I run stateless Databricks commands without preserving cluster state?▼

Yes, you can run stateless Databricks commands via databricks_command to execute single commands on a live cluster without preserving state between individual calls.

Does MCP work with Databricks for validating notebooks and SQL queries?▼

MCP works with Databricks to enable end-to-end validation of notebooks, pipelines, and SQL queries against production-like data while capturing complete, real-cluster outputs.

What are the limitations of stateless testing on Databricks clusters?▼

The limitation of stateless testing on Databricks clusters is that variables and temporary objects do not persist between calls, making it unsuitable for iterative debugging without creating a stateful context.

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