Walk-Forward Efficiency, parameter-stability scoring, and WFO window generation for trading strategies
- ✓Open-source license (MIT)
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- ✓Documented (README)
git clone https://github.com/tylerscomic-lab/walkforward-validator-mcp{
"mcpServers": {
"walkforward-validator-mcp": {
"command": "node",
"args": ["/path/to/walkforward-validator-mcp/dist/index.js"]
}
}
}MCP Servers overview
# walkforward-validator-mcp [](LICENSE) [](https://mcpize.com/mcp/walkforward-validator-mcp) An MCP server for walk-forward analysis of trading strategies — Walk-Forward Efficiency ratio, parameter-stability scoring, lock-after-optimization audits, and WFO window generation. ## The problem this solves A strategy optimized on one historical window and never re-validated on a fresh, unseen window is a curve fit until proven otherwise. Walk-forward analysis is the standard fix, but building the rolling windows correctly and scoring whether a parameter surface is a robust plateau or a fragile spike is easy to get subtly wrong by hand. ## Tools ### `walk_forward_efficiency` Computes the Walk-Forward Efficiency ratio — out-of-sample performance as a fraction of in-sample performance — the core signal for whether an optimization generalizes. ### `parameter_stability_score` Scores a parameter surface for fragile curve-fit spikes vs. robust plateaus, flagging optimizations that only work at one exact parameter value. ### `lock_after_wfo_check` Audits whether parameters were genuinely locked after the walk-forward optimization step, or quietly re-tuned against the "out-of-sample" data — the mistake that silently invalidates a WFO result. ### `walk_forward_window_generator` Generates correctly non-overlapping rolling in-sample/out-of-sample windows for a given date range and step size. ## Use it **Hosted (recommended):** [MCPize](https://mcpize.com/mcp/walkforward-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), [montecarlo-validator-mcp](https://github.com/tylerscomic-lab/montecarlo-validator-mcp), [overfitting-audit-mcp](https://github.com/tylerscomic-lab/overfitting-audit-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 walkforward-validator-mcp
What is tylerscomic-lab/walkforward-validator-mcp?
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tylerscomic-lab/walkforward-validator-mcp is mcp servers for the Claude AI ecosystem. Walk-Forward Efficiency, parameter-stability scoring, and WFO window generation for trading strategies It has 0 GitHub stars and its last recorded update is dated 2026-07-27.
How do I install walkforward-validator-mcp?
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You can install walkforward-validator-mcp by cloning the repository (https://github.com/tylerscomic-lab/walkforward-validator-mcp) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
Is tylerscomic-lab/walkforward-validator-mcp safe to use?
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Our security agent has analyzed tylerscomic-lab/walkforward-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/walkforward-validator-mcp?
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tylerscomic-lab/walkforward-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 walkforward-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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