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View on GitHubDecision audit trail + persistent memory for AI trading agents. Outcome-weighted recall, tamper-evident SHA-256 chain with RFC 3161 anchoring, 20 MCP tools.
Python MCP server that gives AI trading agents persistent trade memory, outcome-weighted recall, risk checks, and a tamper-evident audit trail. Includes a preview broker proxy that evaluates orders against configurable policies before forwarding them.
Use Cases
Record and recall an agent's past tradesReview trade outcomes and behavioral patternsCheck trading decisions against risk limitsMaintain a tamper-evident audit trailSync trade records from MetaTrader 5Place a policy-checking proxy between an agent and a broker MCP server
Built With
- Language
- Python
- Frameworks
- FastMCP · FastAPI · Pydantic · SQLAlchemy · Alembic
Tags
AI trading agents · persistent memory · MCP server · audit trail · outcome-weighted recall · trade records · risk checks · compliance · SHA-256 · strategy evolution