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tradememory-protocol

MCP

Persistent memory and decision audit trail MCP server for AI trading agents with outcome-weighted recall and tamper detection.

by mnemox-ai·mnemox-ai/tradememory-protocol·Python·v0.5.1
86· A
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git clone https://github.com/mnemox-ai/tradememory-protocol
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About

Your trading AI has amnesia. And regulators are starting to notice.

It makes the same mistakes every session. It can't explain why it traded. It forgets everything when the context window ends. Meanwhile, MiFID II is raising the bar for algorithmic decision documentation (Article 17). The EU AI Act demands systematic logging of AI actions (Article 14). Your competitors' agents are learning from every trade.

The AI trading stack is missing a layer. Every MCP server handles execution — placing orders, fetching prices, reading charts. None handle memory.

Your agent can buy 100 shares of AAPL but can't answer: "What happened last time I bought AAPL in this condition?"

Read more on GitHub →
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MIT
Age
3 months
financememory#trading#forex#crypto#audit-trail#outcome-weighted#tamper-detection#ai-agents#evolution-engine#mcp#mt5#outcome-weighted-memory