mcp_create_and_run_job_for_notebook

WHAT IT DOES

What mcp_create_and_run_job_for_notebook does on Databricks MCP Server

AI agents invoke mcp_create_and_run_job_for_notebook 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.

WHY IT NEEDS A POLICY

Why mcp_create_and_run_job_for_notebook needs a policy

This tool triggers execution of a notebook on Databricks serverless compute. While it also creates a job (Write), the dominant and most severe action is running arbitrary notebook code on cloud infrastructure. Misuse could execute malicious code, consume significant compute resources, or cause unintended side effects in connected data systems.

From the tool's definition 'Create and run a Databricks job for a given notebook path using serverless compute' — the tool both creates and immediately executes a notebook job on Databricks infrastructure

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

mcp_create_and_run_job_for_notebook Rate-limited

mcp_create_and_run_job_for_notebook 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": {
    "mcp_create_and_run_job_for_notebook": {
      "limits": [
        {
          "counter": "mcp_create_and_run_job_for_notebook_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-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 mcp_create_and_run_job_for_notebook

What does the mcp_create_and_run_job_for_notebook tool do? +

Create and run a Databricks job for a given notebook path using serverless compute. Returns job/run IDs and Databricks URLs for monitoring. 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 mcp_create_and_run_job_for_notebook? +

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

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

Can I rate-limit mcp_create_and_run_job_for_notebook? +

Yes. Add a rate_limit block to the mcp_create_and_run_job_for_notebook 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_and_run_job_for_notebook completely? +

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

mcp_create_and_run_job_for_notebook 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.