databricks-isv-rest-api

Provide authentication patterns and samples for Databricks REST API integrations.

5|1|Updated Apr 8, 2026
One-click install
npx skills add https://github.com/databricks-solutions/partner-ai-dev-kit --skill databricks-isv-rest-api
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: databricks-isv-rest-api
Source: https://github.com/databricks-solutions/partner-ai-dev-kit/tree/main/skills/rest-api
Command: npx skills add https://github.com/databricks-solutions/partner-ai-dev-kit --skill databricks-isv-rest-api

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Databricks REST API authentication patterns and examples help ISVs implement and validate secure access across PAT, OAuth M2M, and U2M flows, reducing integration risks.

Core Features & Use Cases

  • Standardized authentication patterns for PAT, OAuth M2M, and U2M across Databricks REST endpoints.
  • Guidance for token acquisition and usage including Unity Catalog tests and SQL statement execution validation.
  • Cross-flow validation and troubleshooting with concrete code samples, environment guidance, and common errors.

Quick Start

Run the REST API authentication examples to acquire tokens and call a sample Databricks endpoint.

Frequently Asked Questions about databricks-isv-rest-api

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

FAQPage Schema
How do I authenticate Databricks REST API calls for an ISV integration?

Databricks REST API authentication for ISV integrations uses standardized patterns for PAT, OAuth M2M, and U2M flows. These patterns provide concrete code samples for acquiring tokens and setting base headers to securely access Databricks endpoints.

What's the difference between OAuth M2M and U2M flows for Databricks APIs?

OAuth M2M (machine-to-machine) uses client credentials for automated service-to-service authentication, while U2M (user-to-machine) requires browser-based sign-ins with PKCE support for interactive user authentication. Both flows handle token exchange to access Databricks REST endpoints.

When do I need PKCE support for Databricks OAuth authentication?

PKCE support is needed for Databricks OAuth authentication during browser-based U2M sign-in flows. It protects authorization code exchanges by requiring a code verifier and challenge, securing interactive user authentication for REST API access.

Does this Databricks REST API authentication guidance include troubleshooting for common errors?

Yes, Databricks REST API authentication guidance includes cross-flow validation and troubleshooting with concrete code samples, environment guidance, and common errors. It covers token acquisition, base headers, and validation for Unity Catalog tests and SQL statement execution.

Can I use personal access tokens (PAT) for authenticating Databricks REST API integrations?

Yes, PAT is one of the supported authentication patterns for Databricks REST API integrations alongside OAuth M2M and U2M. PAT provides a straightforward token-based method for securing access to Databricks endpoints across different languages.

Why does my OAuth token exchange fail when calling Databricks REST APIs?

OAuth token exchange failures when calling Databricks REST APIs often stem from incorrect base headers, missing PKCE parameters, or environment misconfigurations. The authentication guidance provides deterministic tests and troubleshooting samples to resolve these common errors.