python_lint

THE RISK

High Risk

Why python_lint needs a policy

This tool executes the ruff linter against Python code. The 'auto-fix support' means it can modify source files on disk, going beyond a read-only analysis. It runs an external tool (ruff check) and may apply changes to code, making it Execute (with Write characteristics). Since Execute > Write in severity hierarchy, it is classified as Execute.

From the tool's definition Lint Python code using ruff check with auto-fix support

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

POLICY

How to control python_lint

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

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "python_lint": {
      "limits": [
        {
          "counter": "python_lint_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

python_lint 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.

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

RATE-LIMIT THIS TOOL →

Free to start. No card required.

EXPLORE

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Go deeper

High-risk tools in MCP DevTools Server → Every high-risk tool this server exposes, in one view.
All high-risk MCP tools → Every high-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.
Agent sandbox → Bounding what an agent can execute and where the boundary should sit.
Least privilege for MCP → Granting agents the minimum tool surface the task needs.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →

FAQ

Questions about python_lint

What does the python_lint tool do? +

Lint Python code using ruff check with auto-fix support. It is categorised as a Execute tool in the MCP DevTools 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 python_lint? +

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

What risk level is python_lint? +

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

Can I rate-limit python_lint? +

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

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

python_lint is provided by the MCP DevTools Server MCP server (rshade/mcp-devtools-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every MCP DevTools Server tool call.

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

CHECK YOUR STACK →