install_package · Python REPL MCP Server MCP: Risk & Policy

WHAT IT DOES

What install_package does on Python REPL MCP Server

AI agents invoke install_package to trigger actions in Python REPL MCP Server. 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 install_package needs a policy

Installing packages executes external operations (network fetch + environment modification) that can introduce arbitrary third-party code into the runtime. While it doesn't delete data (not Destructive) or move money (not Financial), it runs an external command with significant side effects — arbitrary code from packages executes in the environment, making this Execute at high severity due to potential supply-chain…

From the tool's definition "Install a Python package using uv" — triggers an external package installation operation that modifies the environment by fetching and installing code from external sources.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

install_package Rate-limited

install_package 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": {
    "install_package": {
      "limits": [
        {
          "counter": "install_package_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 REPL MCP Server, so you can run agents against it safely.

FAQ

Questions about install_package

What does the install_package tool do? +

Install a Python package using uv. It is categorised as a Execute tool in the Python REPL MCP 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 install_package? +

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

What risk level is install_package? +

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

Can I rate-limit install_package? +

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

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

install_package is provided by the Python REPL MCP Server MCP server (piplin-es/mcp-python). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.