Bootstrap Monte Carlo backtest validation + prop-firm challenge pass-probability simulator
- ✓Open-source license (MIT)
- ✓Recently active
- ✓Clear description
- ✓Topics declared
- ✓Documented (README)
git clone https://github.com/tylerscomic-lab/montecarlo-validator-mcp{
"mcpServers": {
"montecarlo-validator-mcp": {
"command": "node",
"args": ["/path/to/montecarlo-validator-mcp/dist/index.js"]
}
}
}MCP Servers overview
# montecarlo-validator-mcp [](LICENSE) [](https://mcpize.com/mcp/montecarlo-validator-mcp) An MCP server that statistically validates whether a backtest's edge is real, using bootstrap-resampling and reshuffling Monte Carlo methodology, plus prop-firm-specific pass-probability simulation. ## The problem this solves A single backtest equity curve tells you what happened on one path through history — it doesn't tell you how likely that result was to happen by chance, or what the range of plausible outcomes looks like on the *next* set of trades. This wraps the actual statistical validation (bootstrap confidence intervals, drawdown-path percentiles, challenge pass-probability simulation) instead of eyeballing one curve. ## Tools ### `monte_carlo_validate` Bootstrap 90% confidence interval on per-trade expected value (flags when the interval includes zero), plus drawdown-path percentiles via reshuffling. ### `expected_value_calculator` Per-trade EV from win rate, average win, and average loss. ### `prop_firm_pass_probability` Simulates challenge pass probability from win-rate/risk-reward/target/drawdown-limit inputs. ### `risk_geometry_comparator` Ranks multiple win-rate/risk-reward geometries by simulated pass rate — surfaces that tight, high-win-rate setups often out-pass high-RR/low-win-rate setups on a fixed-target challenge, independent of raw expected value. ## Use it **Hosted (recommended):** [MCPize](https://mcpize.com/mcp/montecarlo-validator-mcp) — free tier, paid Pro tier for higher limits. **Self-host:** ```bash npm install node server.js ``` ## Part of the AlgoForge suite Prop-firm and quant-validation tools for algo traders: [prop-rules-mcp](https://github.com/tylerscomic-lab/prop-rules-mcp), [trade-journal-mcp](https://github.com/tylerscomic-lab/trade-journal-mcp), [payout-calc-mcp](https://github.com/tylerscomic-lab/payout-calc-mcp), [econ-calendar-mcp](https://github.com/tylerscomic-lab/econ-calendar-mcp), [overfitting-audit-mcp](https://github.com/tylerscomic-lab/overfitting-audit-mcp), [walkforward-validator-mcp](https://github.com/tylerscomic-lab/walkforward-validator-mcp), [pinescript-audit-mcp](https://github.com/tylerscomic-lab/pinescript-audit-mcp), [backtest-cost-sensitivity-mcp](https://github.com/tylerscomic-lab/backtest-cost-sensitivity-mcp), [pinescript-mcp](https://github.com/tylerscomic-lab/pinescript-mcp). ## License MIT
What people ask about montecarlo-validator-mcp
What is tylerscomic-lab/montecarlo-validator-mcp?
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tylerscomic-lab/montecarlo-validator-mcp is mcp servers for the Claude AI ecosystem. Bootstrap Monte Carlo backtest validation + prop-firm challenge pass-probability simulator It has 0 GitHub stars and its last recorded update is dated 2026-07-27.
How do I install montecarlo-validator-mcp?
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You can install montecarlo-validator-mcp by cloning the repository (https://github.com/tylerscomic-lab/montecarlo-validator-mcp) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
Is tylerscomic-lab/montecarlo-validator-mcp safe to use?
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Our security agent has analyzed tylerscomic-lab/montecarlo-validator-mcp and assigned a Trust Score of 90/100 (tier: Verified). See the full breakdown of passed checks and flags on this page.
Who maintains tylerscomic-lab/montecarlo-validator-mcp?
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tylerscomic-lab/montecarlo-validator-mcp is maintained by tylerscomic-lab. The last recorded GitHub activity is dated 2026-07-27, with 0 open issues.
Are there alternatives to montecarlo-validator-mcp?
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Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.
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