Databricks MCP integration for AI agents.

Connect AI agents to Databricks through 36 structured actions, including get cluster, create cluster, cancel run, and put secret. Review authentication, inpu…

ACTION CONTRACTS
36
AUTHENTICATION
API key
SOURCE STATUS
Provider-backed

CATALOG SOURCE REVIEWED AUGUST 23, 2026 / ACTION NAMES AND SCHEMAS DERIVED FROM WORKING MACHINES PROVIDER SOURCE

CAPABILITY PROFILE

What the Databricks integration exposes

The Databricks Agent App exposes 36 provider-backed actions for data and developer tools work. Its current contract lets an authorized agent get one databricks cluster by cluster id, create a databricks cluster from a raw clusters/create payload, and cancel a databricks job run by run id. These operations are called through Working Machines as typed capabilities rather than through browser navigation or copied UI steps.

A connection uses API key. Before execution, the agent can inspect the selected action, its required fields, declared scopes, and expected output contract. Provider credentials remain inside the Working Machines runtime; the calling agent receives the capability and its structured result, not the underlying secret.

For reliable operation, start with the narrowest action that satisfies the task, resolve stable provider identifiers before changing state, and validate the returned object or status after execution. Availability still depends on the connected Databricks account, granted provider permissions, workspace policy, region, plan, and upstream API behavior.

VERIFIED ACTION SAMPLE

Real Databricks capabilities.

Showing 12 of 36 actions. Risk labels are conservative signals based on operation names, not substitutes for provider documentation or runtime policy.

get_clusterREAD

Get one Databricks cluster by cluster ID.

INPUTS: clusterId

create_clusterWRITE

Create a Databricks cluster from a raw clusters/create payload.

INPUTS: cluster

cancel_runHIGH IMPACT

Cancel a Databricks job run by run ID.

INPUTS: runId

put_secretREVIEW

Create or overwrite a Databricks secret value.

INPUTS: scope / key / stringValue / bytesValue

create_jobWRITE

Create a Databricks job from a raw Jobs API settings object.

INPUTS: settings

create_repoWRITE

Create a Databricks workspace repo linked to a Git remote.

INPUTS: url / path / provider / branch / tag

create_secret_scopeWRITE

Create a Databricks secret scope.

INPUTS: scope / scopeBackendType / backendAzureKeyvault / initialManagePrincipal

delete_jobHIGH IMPACT

Delete a Databricks job by ID.

INPUTS: jobId

delete_repoHIGH IMPACT

Delete a Databricks workspace repo by repo ID.

INPUTS: repoId

delete_secretHIGH IMPACT

Delete one Databricks secret value.

INPUTS: scope / key

delete_secret_scopeHIGH IMPACT

Delete a Databricks secret scope by scope name.

INPUTS: scope

edit_clusterWRITE

Edit an existing Databricks cluster by cluster ID.

INPUTS: clusterId / cluster

INPUT CONTRACTS

Know what the action needs before it runs.

get_cluster

clusterIdREQUIRED
The Databricks cluster ID.

create_cluster

clusterREQUIRED
A raw Databricks API object.

cancel_run

runIdREQUIRED
The Databricks run ID.

put_secret

scopeREQUIRED
The Databricks secret scope name.
keyREQUIRED
The Databricks secret key name.
stringValueOPTIONAL
UTF-8 secret value.
bytesValueOPTIONAL
Bytes secret value.

PROVIDER-SPECIFIC WORKFLOWS

Jobs this Agent App can support

Inspect Get Cluster

Get one Databricks cluster by cluster ID. Use this as a bounded discovery step, retain the returned identifier, and avoid expanding the read beyond the task's stated scope.

get_cluster

Control Create Cluster

Create a Databricks cluster from a raw clusters/create payload. Resolve the target first, present material changes for confirmation, and make retries idempotent where the provider supports it.

create_cluster

Verify with Create Cluster

Create a Databricks cluster from a raw clusters/create payload. Compare the returned provider state with the intended outcome and preserve stable IDs or canonical links in the run record.

create_cluster

SAFETY BOUNDARY

Operate Databricks with explicit limits

  • Authorize Databricks with API key and grant only the provider access required by the selected actions.
  • 18 actions are change-capable by name. Confirm the target identity and material parameters before allowing a write.
  • Treat `cancel_run`, `delete_job`, and `delete_repo` as high-impact operations and require an explicit approval boundary.
  • No provider scope string is declared on the sampled actions. Verify the connected account's actual permissions in Databricks rather than assuming unrestricted access.
  • After a call, inspect the structured result and execution record before reporting that the Databricks task completed successfully.

CONNECTION MODEL

API key

Databricks personal access token used with the Authorization Bearer header.

Working Machines stores provider credentials behind the execution boundary. An agent can use an authorized connection identity, but catalog discovery alone does not reveal OAuth tokens, API keys, or provider secrets.

READ SIGNALS
16
WRITE SIGNALS
11
HIGH IMPACT
7
REVIEW SIGNALS
2

EVIDENCE AND AVAILABILITY

Provider reference

Action names, input fields, authentication types, and counts on this page are generated from the Working Machines provider catalog. Provider behavior, quotas, object semantics, account eligibility, and regional availability remain governed by Databricks.

Official Databricks website

ONE CONNECTION. REAL WORK.

Give your agent software it can use.

Connect through MCP or explore the Agent App catalog and choose only the capabilities your workflow needs.

EXPLORE AGENT APPS