TradeMemory Protocol

Example Use Cases

• 1

  Persistent memory of past trades to avoid repeating mistakes.

• 2

  Outcome-weighted recall to adjust strategies based on historical performance.

• 3

  Behavioral bias detection and context-aware position sizing.

Description

TradeMemory Protocol enables AI trading agents to record, recall, and learn from past trades using a novel Outcome-Weighted Memory (OWM) system. It supports trade journaling, behavioral bias detection, context-aware position sizing, and strategy adjustments, allowing agents to avoid repeating mistakes and optimize performance over time. The server integrates with multiple MCP clients and brokers, offering a comprehensive memory and reflection framework for sequential financial decision-making.