pyenv

Manages Python versions via pyenv.

SERVERTest SOURCEDave-London/Pare

High RISK CLASS

Category Execute

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-dave-london-pare-test/pyenv.md

WHAT IT DOES

What pyenv does on Test

AI agents invoke pyenv to trigger actions in Test. 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.

RISK

Why pyenv is rated High

Managing Python versions via pyenv involves executing shell commands to install, switch, or configure Python runtime environments. This constitutes external process execution with potentially broad system-level effects, such as changing the active Python version globally or locally, installing new runtimes, or modifying shell configurations. Misuse could affect all Python-dependent processes on the system.

From the tool's definition Manages Python versions via pyenv

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs pyenv safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Test, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For pyenv, this is the rule to start with:

pyenv Rate-limited

pyenv 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": {
    "pyenv": {
      "limits": [
        {
          "counter": "pyenv_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Test, apply this rule, and every pyenv call is checked against it from then on.

FAQ

Questions about pyenv

What does the pyenv tool do? +

Manages Python versions via pyenv. It is categorised as a Execute tool in the Test MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on pyenv? +

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

What risk level is pyenv? +

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

Can I rate-limit pyenv? +

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

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

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

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