databricks_edit_cluster

A write tool on the Databricks MCP server.

SERVERDatabricks MCP Server SOURCEpypi:databricks-sdk-mcp

Medium RISK CLASS

Category Write

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-pramodbhatofficial-databricks-sdk-mcp/databricks-edit-cluster.md

WHAT IT DOES

What databricks_edit_cluster does on Databricks MCP Server

AI agents use databricks_edit_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.

RISK

Why databricks_edit_cluster is rated Medium

The tool modifies cluster settings (configuration, sizing, networking, etc.) which affects running workloads and infrastructure state. These changes are reversible (can be edited again), not destructive, making it Write category. Severity is high because cluster modifications can impact production workloads, data processing pipelines, and cost.

From the tool's definition Tool name 'databricks_edit_cluster' indicates modification of cluster configuration. In the Databricks ecosystem context with 263 tools spanning compute, jobs, and infrastructure management, 'edit' semantically maps to reversible modification operations.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs databricks_edit_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 databricks_edit_cluster, this is the rule to start with:

databricks_edit_cluster Rate-limited

databricks_edit_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": {
    "databricks_edit_cluster": {
      "limits": [
        {
          "counter": "databricks_edit_cluster_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

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 databricks_edit_cluster call is checked against it from then on.

FAQ

Questions about databricks_edit_cluster

What does the databricks_edit_cluster tool do? +

databricks_edit_cluster is a write tool on the Databricks MCP Server MCP server. 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 databricks_edit_cluster? +

Register the Databricks MCP Server MCP server in PolicyLayer and add a rule for databricks_edit_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 databricks_edit_cluster? +

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

Can I rate-limit databricks_edit_cluster? +

Yes. Add a rate_limit block to the databricks_edit_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 databricks_edit_cluster completely? +

Set action: deny in the PolicyLayer policy for databricks_edit_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 databricks_edit_cluster? +

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

KEEP EXPLORING

More on Databricks MCP Server, and thousands of servers like it.

This server

All 262 Databricks MCP Server tools →

Across the catalogue

edit_screen on Stitch MCP Server → The MCP Attack Database →

Guides

Govern customer-ops agents →Argument validation →Scoped token →