showcase

The code effectively uses environment variables for sensitive tokens (`HF_TOKEN`) and avoids direct `eval()` or `exec()` calls. Input validation for tool arguments relies on the LLM's generated JSON, which is then parsed safely with `json.loads()`. The primary security consideration is the LLM's behavior in tool selection; while the system prompt emphasizes `verify_customer_pin` for sensitive operations, a sophisticated prompt injection could theoretically attempt to bypass this. However, the client code itself passes these tool calls to a backend MCP server, which would ideally enforce its own access controls. The `MCP_SERVER_URL` is configurable, preventing hardcoded external dependencies, but controlling this environment variable is crucial for security. Overall, the client-side code demonstrates good security practices for an LLM agent.