vet · Python MCP: Risk & Policy

WHAT IT DOES

What vet does on Python

AI agents invoke vet 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 vet needs a policy

The tool executes the 'go vet' command, which is an external program invocation performing static analysis on code. While it is read-only in nature (no file modifications), it runs an external process whose effects depend on the arguments passed, placing it in the Execute category. Severity is medium as it runs arbitrary go vet analysis which could be directed at any code.

From the tool's definition Runs go vet and returns structured static analysis diagnostics

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

vet Rate-limited

vet 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": {
    "vet": {
      "limits": [
        {
          "counter": "vet_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 vet

What does the vet tool do? +

Runs go vet and returns structured static analysis diagnostics with analyzer names. Uses -json flag for native JSON output with automatic text fallback. 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 vet? +

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

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

Can I rate-limit vet? +

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

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

vet 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

vet 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 →