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Tradememory Protocol

@mnemox-ai

代码仓库

关于 Tradememory Protocol

Structured 3-layer memory system for AI trading agents. L1 records every trade automatically. L2 discovers patterns via reflection engine. L3 evolves strategy in real-time. Built on MCP. Supports MT5, Binance, Alpaca. Python/FastAPI/SQLite. MIT licensed.

#trading#finance#memory#ai-agent#python#mt5#forex#algorithmic-trading

基本信息

分类

其他

传输方式

stdio

发布者

mnemox-ai

提交者

琮琮 彭

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "tradememory": {
      "command": "uvx",
      "args": [
        "tradememory-protocol"
      ]
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Tradememory Protocol?

Tradememory Protocol is a structured 3-layer memory system for AI trading agents. It automatically records every trade (L1), discovers patterns via a reflection engine (L2), and evolves strategy in real-time (L3). Built on MCP, it supports MT5, Binance, and Alpaca exchanges. Implemented in Python/FastAPI with SQLite storage. MIT licensed.

How to use Tradememory Protocol?

As an MCP server, Tradememory Protocol is invoked by compatible MCP clients. The implementation uses Python, FastAPI, and SQLite. It supports configuration for MetaTrader 5 (MT5), Binance, and Alpaca exchanges. No specific commands or config keys are documented in the README.

Key features of Tradememory Protocol

  • 3-layer memory for trading agents
  • L1 records every trade automatically
  • L2 discovers patterns via reflection engine
  • L3 evolves strategy in real-time
  • Supports MT5, Binance, Alpaca exchanges
  • Built on MCP with Python/FastAPI/SQLite

Use cases of Tradememory Protocol

  • Automatically record every trade made by an AI trading agent

评论

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