Clear a REPL session's state and history. Args: session_id: Session ID to clear
AI agents call clear_session to permanently remove resources in MCP Python Interpreter — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
Clearing a session's state and history is an irreversible operation — all variables, imports, and execution history within that session are permanently lost. While it doesn't delete files or external data, the in-memory state and history cannot be recovered after clearing, making it Destructive rather than Write.
From the tool's definition Clear a REPL session's state and history
Documented attack patterns abuse exactly the kind of access clear_session 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 clear_session:
{
"version": "1",
"default": "deny",
"hide": [
"clear_session"
]
} clear_session disappears from the agent's tool list entirely, and any attempt to call it is denied. The rest of the server keeps working.
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Clear a REPL session's state and history. Args: session_id: Session ID to clear. It is categorised as a Destructive tool in the MCP Python Interpreter MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the MCP Python Interpreter MCP server in PolicyLayer and add a rule for clear_session: 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.
clear_session is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the clear_session 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 clear_session. 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.
clear_session 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.