Execute a snippet of Python code and return the output or error.
AI agents invoke run_python_code to trigger actions in Simple MCP. 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 allows arbitrary Python code execution, which gives an AI agent the ability to run any Python command including file I/O, system calls, network operations, data exfiltration, and more. The blast radius is maximal since Python can invoke shell commands, modify files, access credentials, and perform destructive operations.
From the tool's definition Tool name is 'run_python_code' and description states 'Execute a snippet of Python code and return the output or error.' The word 'Execute' directly indicates code execution capability.
Attacks that exploit this kind of access
Execute a snippet of Python code and return the output or error. It is categorised as a Execute tool in the Simple MCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Simple MCP server in PolicyLayer and add a rule for run_python_code: 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 Simple MCP. Nothing to install.
run_python_code 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_code 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_code. 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_code is provided by the Simple MCP server (karar-hayder/simple-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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