execute_command · Iris Execute MCP: Risk & Policy

WHAT IT DOES

What execute_command does on Iris Execute

AI agents invoke execute_command to trigger actions in Iris Execute. 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 execute_command needs a policy

Although the description is empty, the tool name 'execute_command' combined with the server's stated purpose of providing execution capabilities (ObjectScript, class methods, unit tests) and the presence of sibling execution tools leaves little doubt this tool executes arbitrary commands. This falls into the Execute category because it runs code/commands whose effects depend on the arguments provided.

From the tool's definition Tool name is 'execute_command' on a server described as providing 'ObjectScript execution' capabilities. Sibling tools include 'execute_classmethod' and 'execute_unit_tests', which confirm this server executes code.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

execute_command Rate-limited

execute_command 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": {
    "execute_command": {
      "limits": [
        {
          "counter": "execute_command_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 Iris Execute, so you can run agents against it safely.

FAQ

Questions about execute_command

What does the execute_command tool do? +

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

How do I enforce a policy on execute_command? +

Register the Iris Execute MCP server in PolicyLayer and add a rule for execute_command: 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 Iris Execute. Nothing to install.

What risk level is execute_command? +

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

Can I rate-limit execute_command? +

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

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

execute_command is provided by the Iris Execute MCP server (jbrandtmse/iris-execute-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.