Memento implements a planner-executor architecture with case-based reasoning for LLM agents. The system maintains a memory store that accumulates agent experiences and retrieves relevant past cases to inform current decisions, enabling agents to learn from their history without modifying underlying model parameters. It supports MCP tool integration and vLLM for local LLM serving, with evaluations conducted on the GAIA benchmark.