Azure Databricks Data Engineering
Manage Azure Databricks clusters, jobs, and workspace objects for data engineering workflows. Used by data engineers and platform administrators.
What You Can Do
MCP Tools
create-cluster
Create a new Databricks cluster
list-clusters
List all Databricks clusters
get-cluster
Get details of a specific cluster
edit-cluster
Edit cluster configuration
start-cluster
Start a terminated cluster
restart-cluster
Restart a running cluster
terminate-cluster
Terminate a running cluster
delete-cluster
Permanently delete a cluster
list-spark-versions
List available Spark runtime versions
list-node-types
List available node types
create-job
Create a new Databricks job
list-jobs
List all Databricks jobs
get-job
Get job details
update-job
Partially update job settings
delete-job
Delete a job
run-job-now
Trigger a one-time job run
list-job-runs
List job runs
get-job-run
Get details of a specific job run
cancel-job-run
Cancel a running job
get-job-run-output
Get the output of a completed job run
list-workspace-objects
List workspace objects in a directory
get-workspace-object-status
Get status of a workspace object
create-workspace-directory
Create a directory in the workspace
delete-workspace-object
Delete a workspace object
import-workspace-object
Import a notebook or file into the workspace
export-workspace-object
Export a notebook or file from the workspace