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MCPAUDITOPEN SOURCE
TradeMemory Protocol
Persistent memory + audit trail for AI trading agents
The industry's first MCP-native memory layer for AI trading agents. 5 memory types (episodic, semantic, procedural, affective, prospective), outcome-weighted recall, and SHA-256 tamper-proof decision records. Open source, MIT licensed, 1,233 tests.
1,233Tests Passing
17MCP Tools
35+REST Endpoints
SHA-256Tamper Detection
THE CHALLENGE
AI trading agents start every session from zero
No memory of past trades. No context for decisions. No audit trail for compliance. Every session is a blank slate, repeating the same mistakes. Prop firms need compliance-grade logging, but existing tools cost $100K+/year and were never designed for AI agents.
THE SOLUTION
5-layer outcome-weighted memory architecture
Episodic Memory
Every trade stored with full decision context and power-law decay
Semantic Memory
Bayesian strategy beliefs auto-updated from trade outcomes
Affective State
EWMA confidence tracking + drawdown-linked risk appetite
Audit Trail
SHA-256 tamper-proof decision records aligned with MiFID II
IN ACTION
TradeMemory Protocol
RESULTS
6 months
Dev time saved vs in-house build
100%
Decision audit coverage
0
Compliance gaps
PythonFastAPISQLiteMCPClaude APISHA-256PostgreSQLpytest
Want something like this for your trading operation?
▸ Founder-led builds — limited availability