mcp_create_job · Databricks MCP Server MCP: Risk & Policy

WHAT IT DOES

What mcp_create_job does on Databricks MCP Server

AI agents use mcp_create_job 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 mcp_create_job needs a policy

This tool creates a new job resource in Databricks, which is a reversible write operation—jobs can be deleted or modified afterward. However, the severity is high because a malicious agent could create jobs that consume significant computational resources, incur costs, or execute arbitrary workloads depending on the job configuration passed as arguments.

From the tool's definition Tool creates a Databricks job via 'Create a Databricks job' description. The verb 'create' indicates data modification. Job configuration can specify compute resources and execution parameters.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

mcp_create_job Rate-limited

mcp_create_job 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": {
    "mcp_create_job": {
      "limits": [
        {
          "counter": "mcp_create_job_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

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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 mcp_create_job

What does the mcp_create_job tool do? +

Create a Databricks job. If job_config doesn't specify a cluster, serverless compute will be used. 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 mcp_create_job? +

Register the Databricks MCP Server MCP server in PolicyLayer and add a rule for mcp_create_job: 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 mcp_create_job? +

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

Can I rate-limit mcp_create_job? +

Yes. Add a rate_limit block to the mcp_create_job 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 mcp_create_job completely? +

Set action: deny in the PolicyLayer policy for mcp_create_job. 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 mcp_create_job? +

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