clean

THE RISK

Critical Risk

Why clean needs a policy

dotnet clean irreversibly deletes build output directories and compiled artifacts. While source code is not affected, the deletion of build outputs is a destructive, non-reversible operation (without rebuilding). This warrants the Destructive category, with medium severity since only build artifacts are removed, not source data.

From the tool's definition 'Runs dotnet clean to remove build outputs' — removes/deletes compiled build artifacts and outputs

Documented attack patterns abuse exactly the kind of access clean gives an agent:

POLICY

How to control clean

PolicyLayer is an MCP gateway — it sits between your AI agents and Python, and nothing reaches the server without passing your rules. This is the rule we recommend for clean:

policy.json

{
  "version": "1",
  "default": "deny",
  "hide": [
    "clean"
  ]
}

clean disappears from the agent's tool list entirely, and any attempt to call it is denied. The rest of the server keeps working.

Create a free account and register Python — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

RESTRICT THIS TOOL →

Free to start. No card required.

EXPLORE

Related tools and policies

More Python tools

Destructive remove Runs Destructive reset Resets the current HEAD to a specified state. Supports soft, mixed, hard, merge, and keep Destructive secret-delete Deletes a repository, organization, or environment GitHub Actions secret. Destructive tag Manages git tags. Supports list (default), create, and delete actions. List returns struct Destructive variable-delete Deletes a repository, organization, or environment GitHub Actions variable. Destructive workspace Manages Terraform workspaces: list, select, create, or delete workspaces. Destructive package-clean Cleans Swift package build artifacts and returns structured result. Destructive branch Lists, creates, renames, or deletes branches. Returns structured branch data. Pass

All 202 Python tools →

Destructive tools on other servers

Android Forensics ADB MCP Server create_full_backup 0xarchive web3_revoke_key Frida Game Hacking MCP clear_scan cPanel MCP Server clear_spam_box

Go deeper

Govern code and CI agents → Branch allowlists, approval on merges, and rate caps on the build and pipeline tools agents trigger.
Critical-risk tools in Python → Every critical-risk tool this server exposes, in one view.
All critical-risk MCP tools → Every critical-risk tool across the catalogue, and the policy pattern that contains them.
The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Blast radius → How much damage one compromised or confused agent can do — and how to bound it.
Tool call approval → Approval gates on individual tool calls: auto-allow, prompt, or deny.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →
PolicyLayer vs alternatives → How deterministic, per-call MCP policy compares with gateways, identity layers, and authorisation platforms.

FAQ

Questions about clean

What does the clean tool do? +

Runs dotnet clean to remove build outputs and returns structured results. It is categorised as a Destructive tool in the Python MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.

How do I enforce a policy on clean? +

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

What risk level is clean? +

clean is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.

Can I rate-limit clean? +

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

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

clean is provided by the Python MCP server (Dave-London/Pare). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Python tool call.

Start from Python, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

CHECK YOUR STACK →