Execute a Python file (always uses subprocess for file execution). Args: file_path: Path to the Python file to execute environment: Name of the Python environment to use arguments: List of command-line arguments to pass to the script timeout: Maximum execution time in seconds (default: 300)
AI agents invoke run_python_file to trigger actions in MCP Python Interpreter. 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.
This tool runs arbitrary Python code via subprocess, which can execute any external commands, modify system state, exfiltrate data, or cause harm depending on script contents and arguments. The ability to pass arguments and select Python environments amplifies the attack surface.
From the tool's definition Tool description states 'Execute a Python file' and 'uses subprocess for file execution', enabling arbitrary code execution through Python scripts with configurable arguments and timeout.
Documented attack patterns abuse exactly the kind of access run_python_file 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 run_python_file:
{
"version": "1",
"default": "deny",
"tools": {
"run_python_file": {
"limits": [
{
"counter": "run_python_file_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}run_python_file 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.
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Execute a Python file (always uses subprocess for file execution). Args: file_path: Path to the Python file to execute environment: Name of the Python environment to use arguments: List of command-line arguments to pass to the script timeout: Maximum execution time in seconds (default: 300). It is categorised as a Execute tool in the MCP Python Interpreter MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the MCP Python Interpreter MCP server in PolicyLayer and add a rule for run_python_file: 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.
run_python_file is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the run_python_file 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 run_python_file. 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.
run_python_file 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.
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10 MCP Python Interpreter tools catalogued and risk-classified — across an index of 42,500+ MCP servers.