create_job_from_file | PolicyLayer

WHAT IT DOES

What create_job_from_file does on Cloudera Machine Learning (CML) MCP Server

AI agents use create_job_from_file to create or update resources in Cloudera Machine Learning (CML) MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Cloudera Machine Learning (CML) MCP Server environment.

WHY IT NEEDS A POLICY

Why create_job_from_file needs a policy

Based on the name and server context, this tool likely creates (writes) a new job definition from a file. Creating jobs can have significant impact as jobs execute code/processes, making severity high. However, the empty description lowers confidence — it could also trigger execution depending on implementation.

From the tool's definition Tool name 'create_job_from_file' and server context mentions 'scheduling jobs' and 'uploading files'. Sibling tools include 'create_job', suggesting this creates/schedules a job from a file.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

create_job_from_file Rate-limited

create_job_from_file 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": {
    "create_job_from_file": {
      "limits": [
        {
          "counter": "create_job_from_file_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 Cloudera Machine Learning (CML) MCP Server, so you can run agents against it safely.

FAQ

Questions about create_job_from_file

What does the create_job_from_file tool do? +

create_job_from_file. It is categorised as a Write tool in the Cloudera Machine Learning (CML) 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 create_job_from_file? +

Register the Cloudera Machine Learning (CML) MCP Server MCP server in PolicyLayer and add a rule for create_job_from_file: 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 Cloudera Machine Learning (CML) MCP Server. Nothing to install.

What risk level is create_job_from_file? +

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

Can I rate-limit create_job_from_file? +

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

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

create_job_from_file is provided by the Cloudera Machine Learning (CML) MCP Server MCP server (yw449/cloudera-cml-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.