mnemox-ai/tradememory-protocol
Decision audit trail + persistent memory for AI trading agents. Outcome-weighted recall, SHA-256 tamper detection, 17 MCP tools.
Platform-specific configuration:
{
"mcpServers": {
"tradememory-protocol": {
"command": "npx",
"args": [
"-y",
"tradememory-protocol"
]
}
}
}Add the config above to .claude/settings.json under the mcpServers key.
<!-- mcp-name: io.github.mnemox-ai/tradememory-protocol -->
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What if your trading bot could learn from every mistake — and invent better strategies by itself?
200+ trading MCP servers execute trades. None of them remember what happened.
TradeMemory is the memory layer that changes that.
[](https://pypi.org/project/tradememory-protocol/) [](https://github.com/mnemox-ai/tradememory-protocol/actions) [](https://smithery.ai/server/io.github.mnemox-ai/tradememory-protocol) [](https://opensource.org/licenses/MIT) [](https://smithery.ai/server/io.github.mnemox-ai/tradememory-protocol)
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"Why does my bot keep making the same mistakes?"
Persistent memory records every trade with full context — entry reasoning, market regime, confidence level, outcome. Pattern discovery finds what you can't see manually.
"My strategy worked for months, then suddenly stopped."
Outcome-weighted recall auto-downweights patterns from old regimes. Your bot adapts without you rewriting a single rule.
"How do I know it's not just overfitting?"
Every pattern carries B
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