get_cluster

THE RISK

Low Risk

Why get_cluster needs a policy

This tool retrieves cluster information without side effects. It performs a simple lookup operation (get) that returns data about an existing cluster. No cluster state is modified, no jobs are triggered, and no data is created or deleted. This is a straightforward Read operation with minimal security risk.

From the tool's definition Tool name 'get_cluster' and description 'Get information about a specific Databricks cluster' indicate retrieval of cluster metadata.

Documented attack patterns abuse exactly the kind of access get_cluster gives an agent:

POLICY

How to control get_cluster

PolicyLayer is an MCP gateway — it sits between your AI agents and Databricks MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for get_cluster:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "get_cluster": {}
  }
}

get_cluster is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.

Create a free account and register Databricks MCP Server — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

CAP THIS TOOL →

Free to start. No card required.

EXPLORE

Related tools and policies

More Databricks MCP Server tools

Destructive terminate_cluster Terminate a Databricks cluster with parameter: cluster_id (required) Execute execute_sql Execute a SQL statement with parameters: statement (required), warehouse_id (required), ca Execute run_job Run a Databricks job with parameters: job_id (required), notebook_params (optional) Execute start_cluster Start a terminated Databricks cluster with parameter: cluster_id (required) Write create_cluster Create a new Databricks cluster with parameters: cluster_name (required), spark_version (r Read list_clusters List all Databricks clusters Read list_files List files and directories in a DBFS path with parameter: dbfs_path (required) Read list_jobs List all Databricks jobs

All 11 Databricks MCP Server tools →

Read tools on other servers

M-Team MCP Server get_torrent_detail YouTube MCP Server search_channel Android Forensics ADB MCP Server parse_browser_history 0xarchive web3_challenge

Go deeper

The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Data exfiltration → How read access becomes an exfiltration channel when chained with untrusted content.
MCP token cost → What connecting this server costs in context-window tokens on every request.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →

FAQ

Questions about get_cluster

What does the get_cluster tool do? +

Get information about a specific Databricks cluster with parameter: cluster_id (required). It is categorised as a Read tool in the Databricks MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on get_cluster? +

Register the Databricks MCP Server MCP server in PolicyLayer and add a rule for get_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 get_cluster? +

get_cluster is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit get_cluster? +

Yes. Add a rate_limit block to the get_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 get_cluster completely? +

Set action: deny in the PolicyLayer policy for get_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 get_cluster? +

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

Enforce policy on every Databricks MCP Server tool call.

Start from Databricks MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

CHECK YOUR STACK →