patch_file · Cloudera Machine Learning (CML) MCP Server MCP

WHAT IT DOES

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

AI agents use patch_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 patch_file needs a policy

The 'patch' operation modifies file content reversibly within a CML environment. This is a Write action (not Destructive, as patches are typically non-destructive modifications). Severity is medium because unintended file modifications in a machine learning context could affect model artifacts, configurations, or scripts, but impact is bounded to individual files without system-wide blast radius.

From the tool's definition Tool name 'patch_file' indicates modification of file content. Description is empty, limiting direct confirmation, but 'patch' universally means applying changes to existing data.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

patch_file Rate-limited

patch_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": {
    "patch_file": {
      "limits": [
        {
          "counter": "patch_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 patch_file

What does the patch_file tool do? +

patch_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 patch_file? +

Register the Cloudera Machine Learning (CML) MCP Server MCP server in PolicyLayer and add a rule for patch_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 patch_file? +

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

Can I rate-limit patch_file? +

Yes. Add a rate_limit block to the patch_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 patch_file completely? +

Set action: deny in the PolicyLayer policy for patch_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 patch_file? +

patch_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.