sync_repo_and_run_notebook · Databricks MCP Server MCP

WHAT IT DOES

What sync_repo_and_run_notebook does on Databricks MCP Server

AI agents invoke sync_repo_and_run_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 sync_repo_and_run_notebook needs a policy

This tool executes arbitrary code by running a notebook on a Databricks cluster. The severity is high because notebook execution can trigger complex operations across data infrastructure, potentially affecting data pipelines, triggering jobs, and interacting with Unity Catalog.

From the tool's definition Tool performs 'run a notebook' operation which executes code on Databricks infrastructure. The description explicitly states it will 'Pull a repo then run a notebook' with parameters controlling the notebook_path and execution context (cluster_id,…

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

sync_repo_and_run_notebook Rate-limited

sync_repo_and_run_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": {
    "sync_repo_and_run_notebook": {
      "limits": [
        {
          "counter": "sync_repo_and_run_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 sync_repo_and_run_notebook

What does the sync_repo_and_run_notebook tool do? +

Pull a repo then run a notebook. Parameters: repo_id, notebook_path, existing_cluster_id (optional), base_parameters (optional). 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 sync_repo_and_run_notebook? +

Register the Databricks MCP Server MCP server in PolicyLayer and add a rule for sync_repo_and_run_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 sync_repo_and_run_notebook? +

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

Can I rate-limit sync_repo_and_run_notebook? +

Yes. Add a rate_limit block to the sync_repo_and_run_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 sync_repo_and_run_notebook completely? +

Set action: deny in the PolicyLayer policy for sync_repo_and_run_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 sync_repo_and_run_notebook? +

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