create_cluster · Databricks MCP Server MCP: Risk & Policy

WHAT IT DOES

What create_cluster does on Databricks MCP Server

AI agents use create_cluster to create or update resources in Databricks MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Databricks MCP Server environment.

WHY IT NEEDS A POLICY

Why create_cluster needs a policy

This tool creates new cloud infrastructure (a Databricks cluster) which constitutes a Write operation—reversible resource creation. The severity is high because instantiating clusters incurs compute costs and consumes cloud resources; an AI agent creating many clusters could cause significant financial and resource waste, though the action itself is technically reversible (clusters can be deleted).

From the tool's definition Tool name is "create_cluster" and description states "Create a new Databricks cluster". The verb "Create" and explicit reference to cluster creation indicates data/resource creation with reversible effects.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

create_cluster Rate-limited

create_cluster stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "create_cluster": {
      "limits": [
        {
          "counter": "create_cluster_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Databricks MCP Server, so you can run agents against it safely.

FAQ

Questions about create_cluster

What does the create_cluster tool do? +

Create a new Databricks cluster with parameters: cluster_name (required), spark_version (required), node_type_id (required), num_workers, autotermination_minutes. It is categorised as a Write tool in the Databricks MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on create_cluster? +

Register the Databricks MCP Server MCP server in PolicyLayer and add a rule for create_cluster: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Databricks MCP Server. Nothing to install.

What risk level is create_cluster? +

create_cluster is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit create_cluster? +

Yes. Add a rate_limit block to the create_cluster rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block create_cluster completely? +

Set action: deny in the PolicyLayer policy for create_cluster. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides create_cluster? +

create_cluster is provided by the Databricks MCP Server MCP server (robkisk/databricks-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.