set_job_permissions · Databricks Permissions MCP Server MCP

WHAT IT DOES

What set_job_permissions does on Databricks Permissions MCP Server

AI agents use set_job_permissions to create or update resources in Databricks Permissions MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Databricks Permissions MCP Server environment.

WHY IT NEEDS A POLICY

Why set_job_permissions needs a policy

This tool modifies permissions/access control settings for jobs, which is a reversible Write operation. While permissions changes can have significant security implications (affecting who can access sensitive jobs or data), the action itself is not destructive (permissions can be changed back) and does not directly delete, execute code, or move money.

From the tool's definition Tool name 'set_job_permissions' and description 'Set permissions for a job' indicate modification of access control settings. Parameters include 'job_id' and 'access_control_list', which are used to configure who can access or execute a job.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

set_job_permissions Rate-limited

set_job_permissions 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": {
    "set_job_permissions": {
      "limits": [
        {
          "counter": "set_job_permissions_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

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 Permissions MCP Server, so you can run agents against it safely.

FAQ

Questions about set_job_permissions

What does the set_job_permissions tool do? +

Set permissions for a job with parameters: job_id (required), access_control_list (required). It is categorised as a Write tool in the Databricks Permissions 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 set_job_permissions? +

Register the Databricks Permissions MCP Server MCP server in PolicyLayer and add a rule for set_job_permissions: 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 Permissions MCP Server. Nothing to install.

What risk level is set_job_permissions? +

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

Can I rate-limit set_job_permissions? +

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

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

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