run_episode · MCP4DRL MCP: Risk & Policy

WHAT IT DOES

What run_episode does on MCP4DRL

AI agents invoke run_episode to trigger actions in MCP4DRL. 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 run_episode needs a policy

This tool invokes execution of a trained RL agent within a business process resource allocation simulator. Although the description is empty (lowering confidence slightly), the function name 'run_episode' combined with context (RL simulation framework, sibling execution/control tools) indicates it runs a complete episode of the trained agent, which constitutes code/model execution with side effects on the simulation…

From the tool's definition Tool is named 'run_episode' with empty description; sibling tools include 'step_simulation', 'run_steps', and 'run_with_checkpoints', indicating this tool executes a reinforcement learning episode that runs the Deep Q-Network agent to completion.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

run_episode Rate-limited

run_episode 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": {
    "run_episode": {
      "limits": [
        {
          "counter": "run_episode_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 MCP4DRL, so you can run agents against it safely.

FAQ

Questions about run_episode

What does the run_episode tool do? +

run_episode. It is categorised as a Execute tool in the MCP4DRL MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on run_episode? +

Register the MCP4DRL MCP server in PolicyLayer and add a rule for run_episode: 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 MCP4DRL. Nothing to install.

What risk level is run_episode? +

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

Can I rate-limit run_episode? +

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

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

run_episode is provided by the MCP4DRL MCP server (mostapow/mcp4drl). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.