remote_clean_project · Pistachio MCP Server MCP

WHAT IT DOES

What remote_clean_project does on Pistachio MCP Server

AI agents invoke remote_clean_project to trigger actions in Pistachio MCP Server. 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 remote_clean_project needs a policy

This tool invokes a shell command (./gradlew clean) that executes code on a remote system. While 'clean' is typically a non-destructive build operation that removes build artifacts, it is fundamentally an Execute action because it runs arbitrary external operations on a remote system.

From the tool's definition Tool executes './gradlew clean' command on a remote project, which runs external build system operations whose effects depend on the project configuration and system state.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

remote_clean_project Rate-limited

remote_clean_project 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": {
    "remote_clean_project": {
      "limits": [
        {
          "counter": "remote_clean_project_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 Pistachio MCP Server, so you can run agents against it safely.

FAQ

Questions about remote_clean_project

What does the remote_clean_project tool do? +

Run ./gradlew clean on a remote project and return the output. It is categorised as a Execute tool in the Pistachio MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on remote_clean_project? +

Register the Pistachio MCP Server MCP server in PolicyLayer and add a rule for remote_clean_project: 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 Pistachio MCP Server. Nothing to install.

What risk level is remote_clean_project? +

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

Can I rate-limit remote_clean_project? +

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

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

remote_clean_project is provided by the Pistachio MCP Server MCP server (jack-beanstalk-2022/pistachiomcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.