Analytics and Data

Databricks

Unified data analytics platform that combines data engineering, data science, machine learning, and analytics on a single collaborative lakehouse architecture.

Databricks MCP, Integrations & Automations for Enterprise AI Agents

Connect your AI agents to Databricks MCP in minutes. No field mapping. No code required. Adopt AI's zero-shot API discovery means your agents understand Databricks's schema on first contact - and can act on it instantly.

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What Your AI Agents Can Do

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Get Job Run on Databricks
Gets run metadata (GET 2.1).
SQL Execute And Wait on Databricks
POST statement then poll until SUCCEEDED/FAILED/CANCELED or timeout.
List Job Runs on Databricks
Lists runs for job.
List Pools on Databricks
Lists instance pools.
Repair Run on Databricks
Repairs a failed run.
Create Cluster on Databricks
Creates cluster (pass body_json for full spec).
Statements Cancel on Databricks
Cancel SQL statement.
List Workspace on Databricks
Lists workspace path.
Metrics Query on Databricks
Metrics query preview (body_json).
Create Job on Databricks
Creates job (use body_json).
Run Job And Wait on Databricks
Triggers job then polls run until terminal.
Delete Workspace on Databricks
Delete workspace object.
Get Run Output on Databricks
Gets notebook/task output.
Query Serving Endpoint on Databricks
POST invocations to serving endpoint.
List Clusters on Databricks
Lists all clusters.
Scim Me on Databricks
SCIM me (preview).
Uninstall Library on Databricks
Uninstall from cluster.
Token Create on Databricks
Create PAT (body_json).
Policy Families List on Databricks
Policy families preview.
List Cluster Libraries on Databricks
All cluster library statuses.
Current User on Databricks
Alias current user.
List Pipelines on Databricks
Lists DLT pipelines.
Permissions Update on Databricks
Updates ACLs (body_json).
List Dbfs on Databricks
Lists DBFS path.
Jobs Submit Run on Databricks
Submit one-off run (body_json).
SQL Get Result on Databricks
GET statement status/result by id.
Edit Cluster on Databricks
Edit cluster config.
Global Init Scripts on Databricks
GET global init scripts.
Feature Store List on Databricks
Feature store tables (if enabled).
Model Registry List on Databricks
MLflow registered models.
Delete Cluster on Databricks
Permanent delete cluster.
List Serving Endpoints on Databricks
Lists model serving endpoints.
Get SQL Warehouse on Databricks
Gets SQL warehouse by id.
Dbfs Read on Databricks
Read file chunk.
Get Job on Databricks
Gets job definition.
Mkdirs Dbfs on Databricks
Make directories.

Connect Databricks MCP using Adopt AI in 3 Simple Steps

  1. Run a single command in your terminal to install the Databricks MCP server locally, no complex setup, no cloud dependency.
  2. A browser window opens automatically, where you can securely authenticate with your Databricks account with one click.
  3. Restart your AI client, and your agents instantly have full access to notebooks, clusters, jobs, and every Databricks object, ready to read, write, and automate.

Use Cases for Databricks MCP

1. Automated Data Pipeline Orchestration

AI agents create, schedule, and monitor Databricks jobs and workflows, ensuring data pipelines run on time and alerting teams to failures or delays.


2. Notebook-Based Analysis Automation

AI agents execute Databricks notebooks on demand, passing parameters and collecting results to power automated reporting and ad-hoc analytics workflows.


3. ML Model Training & Deployment

AI agents manage end-to-end ML workflows in Databricks � from data prep and feature engineering to model training, evaluation, and deployment via MLflow.


4. Data Quality Monitoring

AI agents run data quality checks on Databricks tables, flag anomalies, missing values, and schema drift, and generate data health reports for engineering teams.


5. Cost & Cluster Management

AI agents monitor Databricks cluster usage and costs, auto-scale or terminate idle clusters, and generate spend reports to optimize cloud compute budgets.

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Frequently Asked Questions

Do I need my own developer credentials to use Databricks MCP with Adopt AI?

No, you can get started immediately using Adopt AI's built-in Databricks integration. For production use, we recommend configuring your own API tokens for greater control and security.


Can I connect Databricks with other apps through Adopt AI?

Yes! Adopt AI supports multi-app workflows, so your AI agents can seamlessly move data between Databricks and data warehouses, BI tools, cloud platforms, and more.


Is Adopt AI secure?

Absolutely. Adopt AI is SOC 2 Type 2 certified and ISO/IEC 27001 compliant, and adheres to EU GDPR, CCPA, and HIPAA standards. All data is encrypted in transit and at rest, ensuring the confidentiality, integrity, and availability of your data. Learn more here.


What happens if the Databricks API changes?

Adopt AI maintains and updates all integrations automatically, so your agents always work with the latest API versions, no manual maintenance required.


Do I need coding skills to set up the Databricks integration?

Not at all. Adopt AI's zero-shot API discovery means your agents understand Databricks's schema on first contact. Setup takes minutes with no code required.


How do I set up custom Databricks MCP in Adopt AI?

For a step-by-step guide on creating and configuring your own Databricks API tokens with Adopt AI, see here.