check · Python MCP: Risk & Policy

WHAT IT DOES

What check does on Python

AI agents invoke check to trigger actions in Python. 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 check needs a policy

The tool executes an external command (cargo check) which triggers compilation analysis and system-level operations. While it doesn't produce a final build artifact, it still runs an external process whose effects depend on the project being analyzed. This falls under Execute rather than Read because it actively runs a command rather than just querying existing data.

From the tool's definition Runs cargo check (type check without full build) and returns structured diagnostics

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

check Rate-limited

check 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": {
    "check": {
      "limits": [
        {
          "counter": "check_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 Python, so you can run agents against it safely.

FAQ

Questions about check

What does the check tool do? +

Runs cargo check (type check without full build) and returns structured diagnostics. Faster than build for error checking. It is categorised as a Execute tool in the Python MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on check? +

Register the Python MCP server in PolicyLayer and add a rule for check: 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 check? +

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

Can I rate-limit check? +

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

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

check 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.

// THE FULL RECORD

check is one line of Python's registry record.

The record carries the whole server: verified identity, auth posture, risk grade, every tool classified, recommended policy — re-checked continuously.

Teams ship this data inside their own products. See what a licence covers →