TradeMemory — Decision Audit Trail for AI Trading Agents

Binance skills execute trades. TradeMemory records why.

TradeMemory keeps the decision record. When your AI agent opens a position using the Spot or Futures skill, TradeMemory captures the full decision context: what conditions triggered the signal, which filters passed or blocked, the market indicators at that moment, risk state, and execution details. Every record is SHA-256 hashed for tamper detection.

Why keep it. So you, or anyone you report to, can see why each trade was taken and how it ended. Rules that require decision records (MiFID II Article 17) bind investment firms, not retail users; the EU AI Act's high-risk logging obligations were postponed to 2 December 2027, and ESMA's February 2026 briefing states that AI-based algorithmic trading is currently excluded from the high-risk scope. This is not a compliance claim.

What TradeMemory Records

For every trading decision your agent makes:

Real Decision Event

This is a real decision event from a XAUUSD trading system running three automated strategies. The AI agent detected a SHORT breakout signal but the sell_allowed filter blocked execution:

{
  "ts": "2026-03-26 07:55:00",
  "strategy": "VolBreakout",
  "decision": "FILTERED",
  "signal_triggered": true,
  "signal_direction": "SHORT",
  "conditions_json": {
    "conditions": [
      {"name": "breakout_high", "passed": false, "current_value": 4462.58, "threshold": 4569.75, "operator": ">"},
      {"name": "breakout_low", "passed": true, "current_value": 4462.58, "threshold": 4463.11, "operator": "<"}
    ]
  },
  "filters_json": {
    "filters": [
      {"name": "spread_gate", "passed": true, "blocked": false, "current_value": 12.0, "threshold": 0.0},
      {"name": "sell_allowed", "passed": false, "blocked": true, "current_value": 0.0, "threshold": 0.0},
      {"name": "account_risk", "passed": true, "blocked": false, "current_value": 0.0, "threshold": 0.0},
      {"name": "regime_gate", "passed": true, "blocked": false, "current_value": 0.0, "threshold": 0.0}
    ]
  },
  "indicators_json": {
    "atr_d1": 171.16,
    "atr_m5": 8.53,
    "asia_high": 4544.08,
    "asia_low": 4488.78,
    "asia_range": 55.30
  },
  "regime": "TRENDING",
  "regime_ratio": 0.335,
  "consec_losses": 0,
  "cooldown_active": false,
  "risk_daily_pct": 0.0
}

A regulator or risk manager can read this and immediately understand: the agent saw a valid breakout, but policy blocked the SHORT direction. No guessing, no black box.

How It Works with Binance Skills

Your AI Agent
    |
    |--- [1] Binance Spot Skill: execute BUY 0.01 XAUUSD
    |
    |--- [2] TradeMemory Skill: record WHY this trade was made
    |         - conditions that triggered the signal
    |         - filters that passed/blocked
    |         - market indicators at decision time
    |         - risk state and regime context
    |         - SHA-256 hash for tamper detection
    |
    |--- [3] Later: query /audit/verify/{trade_id} to prove the record hasn't been altered

Installation

pip install tradememory-protocol

Start the server:

python -m tradememory
# Server running at http://localhost:8000

API Endpoints

Record a Decision

POST /trade/record_decision
Content-Type: application/json

{
  "trade_id": "VB_20260326_0755",
  "symbol": "XAUUSD",
  "direction": "short",
  "strategy": "VolBreakout",
  "confidence": 0.75,
  "reasoning": "SHORT breakout detected. Price 4462.58 < asia_low 4488.78 - buffer. Blocked by sell_allowed filter.",
  "market_context": {
    "price": 4462.58,
    "session": "london",
    "regime": {"regime": "TRENDING", "atr_h1": 26.66, "atr_d1": 171.16},
    "decision_data": {
      "indicators": {"atr_d1": 171.16, "atr_m5": 8.53, "spread_pts": 12}
    }
  }
}

Audit: Get Decision Record

GET /audit/decision-record/{trade_id}

Returns a complete Trading Decision Record (TDR) with:

• Decision context (who, what, when, why)
• Memory context (similar past trades recalled)
• Market snapshot (indicators, regime, risk)
• SHA-256 data hash

Audit: Verify Integrity

GET /audit/verify/{trade_id}

{
  "trade_id": "VB_20260326_0755",
  "verified": true,
  "stored_hash": "a3f8c9...",
  "computed_hash": "a3f8c9...",
  "match": true
}

Recomputes SHA-256 from stored inputs and compares. If any field was tampered with after recording, match will be false.

Audit: Bulk Export

GET /audit/export?strategy=VolBreakout&start=2026-03-01&end=2026-03-31&format=jsonl

Export all TDRs as JSON or JSONL for review.

Security

• The memory server never asks for exchange or broker keys. It does not execute trades, move funds, or access wallets. (The optional brake that sits in front of a broker is a separate install; see the project README.)
• Read and record only. The agent calls TradeMemory after making a decision, passing the context. TradeMemory stores it.
• Local-first. Records stay in a local SQLite file. Daily audit roots are timestamped by an RFC 3161 authority by default: a 32-byte hash, no trade data (TRADEMEMORY_TSA=off turns it off). The evolution tools read public Binance market data when an agent calls them. The README's Security section lists every outbound call.
• Tamper-evident, not tamper-proof. Every record is hashed at creation and linked to the one before; changing a record breaks the chain. Verify it at any point with /audit/verify.
• Scale: 20 MCP tools, a REST API, and five memory layers (episodic, semantic, procedural, affective, prospective).

Where the records map to regulation

The table shows which TradeMemory features map to these texts if and when they apply to you. It is not a compliance claim.

MCP Integration

TradeMemory also runs as an MCP server with 20 tools:

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

Key MCP tools: remember_trade, recall_memories (with order="losses_first" before a trade), get_strategy_performance, export_audit_trail, verify_audit_hash, verify_audit_chain.

Links

• PyPI: tradememory-protocol
• GitHub: mnemox-ai/tradememory-protocol (MIT license)
• Author: mnemox-ai