start_cluster

Start a terminated Databricks cluster with parameter: cluster_id (string, required)

SERVERDatabricks MCP Server SOURCEandresgarciasobrado91/databricks-mcp-server

High RISK CLASS

Category Execute

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/andresgarciasobrado91-databricks-mcp-server/start-cluster.md

WHAT IT DOES

What start_cluster does on Databricks MCP Server

AI agents invoke start_cluster to trigger actions in Databricks MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.

RISK

Why start_cluster is rated High

This is an Execute risk because it triggers an external operation (cluster startup) with side effects that depend on the provided cluster_id argument. It is not Read (no data retrieval), Write (not creating/modifying data reversibly), Destructive (cluster remains after startup), or Financial (no direct money movement).

From the tool's definition The tool description states 'Start a terminated Databricks cluster' - this initiates and triggers an external operation (cluster startup) whose infrastructure effects depend on the cluster_id argument.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs start_cluster safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Databricks MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For start_cluster, this is the rule to start with:

start_cluster Rate-limited

start_cluster stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "start_cluster": {
      "limits": [
        {
          "counter": "start_cluster_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Databricks MCP Server, apply this rule, and every start_cluster call is checked against it from then on.

FAQ

Questions about start_cluster

What does the start_cluster tool do? +

Start a terminated Databricks cluster with parameter: cluster_id (string, required). It is categorised as a Execute tool in the Databricks MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on start_cluster? +

Register the Databricks MCP Server MCP server in PolicyLayer and add a rule for start_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 start_cluster? +

start_cluster is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit start_cluster? +

Yes. Add a rate_limit block to the start_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 start_cluster completely? +

Set action: deny in the PolicyLayer policy for start_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 start_cluster? +

start_cluster is provided by the Databricks MCP Server MCP server (andresgarciasobrado91/databricks-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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