Backtest a candidate pattern against historical OHLCV data. Takes a pattern dict (from discover_patterns) and runs a vectorized backtest. Returns fitness metrics: Sharpe ratio, win rate, trade count, max drawdown, total PnL. Args: pattern_dict: CandidatePattern as dict (from discover_patter...
Part of the Tradememory Protocol MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents invoke evolution_run_backtest to trigger processes or run actions in Tradememory Protocol. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.
evolution_run_backtest can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. Intercept enforces rate limits and validates arguments to keep execution within safe bounds.
Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.
tools:
evolution_run_backtest:
rules:
- action: allow
rate_limit:
max: 10
window: 60
validate:
required_args: trueSee the full Tradememory Protocol policy for all 15 tools.
Agents calling execute-class tools like evolution_run_backtest have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Execute risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.
evolution_run_backtest is one of the high-risk operations in Tradememory Protocol. For the full severity-focused view — only the high-risk tools with their recommended policies — see the breakdown for this server, or browse all high-risk tools across every MCP server.
Backtest a candidate pattern against historical OHLCV data. Takes a pattern dict (from discover_patterns) and runs a vectorized backtest. Returns fitness metrics: Sharpe ratio, win rate, trade count, max drawdown, total PnL. Args: pattern_dict: CandidatePattern as dict (from discover_patterns output) symbol: Trading pair (e.g. "BTCUSDT") timeframe: Bar timeframe — "5m", "15m", "1h", "4h", "1d" days: Days of history to backtest against (default 90). It is categorised as a Execute tool in the Tradememory Protocol MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Add a rule in your Intercept YAML policy under the tools section for evolution_run_backtest. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Tradememory Protocol MCP server.
evolution_run_backtest is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the evolution_run_backtest rule in your Intercept policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the Intercept policy for evolution_run_backtest. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
evolution_run_backtest is provided by the Tradememory Protocol MCP server (mnemox-ai/tradememory-protocol). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Open source. One binary. Zero dependencies.
npx -y @policylayer/intercept