List all available Python environments (system Python and conda environments).
AI agents call list_python_environments to retrieve information from MCP Python Interpreter without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and enumerates information about available Python environments without executing code, modifying state, or causing side effects. It is a pure read operation similar to the sibling tool 'list_installed_packages' and 'list_directory'. The blast radius is minimal—knowing what Python environments exist poses no direct security risk and does not enable unauthorized actions on its own.
From the tool's definition Tool name 'list_python_environments' and description 'List all available Python environments' indicate a query/retrieval operation with no modification or execution of code.
Documented attack patterns abuse exactly the kind of access list_python_environments gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and MCP Python Interpreter, and nothing reaches the server without passing your rules. This is the rule we recommend for list_python_environments:
{
"version": "1",
"default": "deny",
"tools": {
"list_python_environments": {}
}
}list_python_environments is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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List all available Python environments (system Python and conda environments). It is categorised as a Read tool in the MCP Python Interpreter MCP Server, which means it retrieves data without modifying state.
Register the MCP Python Interpreter MCP server in PolicyLayer and add a rule for list_python_environments: 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 Python Interpreter. Nothing to install.
list_python_environments is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the list_python_environments 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.
Set action: deny in the PolicyLayer policy for list_python_environments. 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.
list_python_environments is provided by the MCP Python Interpreter MCP server (yzfly/mcp-python-interpreter). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 10 MCP Python Interpreter tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
10 MCP Python Interpreter tools catalogued and risk-classified — across an index of 42,500+ MCP servers.