# StratEvo

Quant trading MCP server: quotes, backtests, screening, and a genetic algorithm that breeds and walk-forward validates strategies across 484+ factors.

- MCP server · `type=mcp` · Claude Code, Codex, Cursor, GitHub Copilot, Windsurf (Devin Desktop), Cline, Zed, Gemini CLI · ★ 33
- Author: NeuZhou
- License: not stated · policy=link-only · description only; the file stays with the author
- Source: https://github.com/NeuZhou/stratevo
- Updated: 2026-04-18
- HTML: https://affpapa.org/en/nevibecode/mcp/stratevo

## What it does

This server hands your agent quantitative trading work: price data, backtests, screening, strategy evolution. Coverage is US stocks and crypto.

Strategies aren't authored by hand. Each one is a weight vector over 484+ factors plus risk settings — `hold_days`, `trailing_stop`, how hard to cut exposure when the market turns, `kelly_fraction` for position size. Candidates go through walk-forward runs on several out-of-sample windows, survivors get ranked by Sharpe × Return / MaxDD, then mutated and crossed into the next generation. Guards against curve fitting: 1,000 shuffled Monte Carlo passes, combinatorial purged cross-validation, a penalty on turnover. Roughly 200 of the factors are crypto-native, covering funding rates, liquidations and large-wallet flow.

The returns in the tables come from backtests, not traded money. An early build once showed 25,000% and it turned out to be look-ahead bias. Installing calls `uvx stratevo` under the hood, so `uvx` has to be on the machine first.

## Requirements
- Needs: Python and uv (commands run via uvx)

## Install

### Claude Code (native platform)

**Platform CLI**
```bash
claude mcp add stratevo -- uvx stratevo
```
uvx runs the command named after the package; if the README names another one, use uvx --from stratevo <command>

### Codex

**Platform CLI**
```bash
codex mcp add stratevo -- uvx stratevo
```
uvx runs the command named after the package; if the README names another one, use uvx --from stratevo <command>

### Cursor

**Config file**
File `.cursor/mcp.json`:
```json
{
    "mcpServers": {
        "stratevo": {
            "command": "uvx",
            "args": [
                "stratevo"
            ]
        }
    }
}
```
uvx runs the command named after the package; if the README names another one, use uvx --from stratevo <command>

### GitHub Copilot

**Config file**
File `.vscode/mcp.json`:
```json
{
    "servers": {
        "stratevo": {
            "type": "stdio",
            "command": "uvx",
            "args": [
                "stratevo"
            ]
        }
    }
}
```
uvx runs the command named after the package; if the README names another one, use uvx --from stratevo <command>

### Gemini CLI

**Platform CLI**
```bash
gemini mcp add stratevo uvx stratevo
```
uvx runs the command named after the package; if the README names another one, use uvx --from stratevo <command>

## When to use it
- backtest a strategy across several windows without leaking future bars
- drop candidates that only work on one slice of history
- let the search set factor weights instead of tuning them by hand
- rank strategies by Sharpe with drawdown factored in
- test whether a result survives shuffled market history

## Example prompts
- Run a walk-forward backtest of my momentum strategy on S&P 500 names and report max drawdown
- Evolve twenty strategy candidates across the 484 factors and keep the ones that pass Monte Carlo
- Compare these two strategies on Sharpe and MaxDD, with fees and slippage included

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