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Addresses all findings from DATA_ACCURACY_AUDIT.md: - Fractal-based S/R detection replacing naive percentage approach (wshobson#2/wshobson#10/wshobson#11) - MACD precision 2→4 decimals (wshobson#3), div-by-zero guards in patterns (wshobson#4) - Per-algorithm retry in screening scheduler with data_freshness tracking (wshobson#1) - Cache bypass parameter on all screening endpoints (wshobson#5) - Clean Alpaca date index offset (wshobson#6), NaN for missing volume (wshobson#7) - VWAP daily approximation (wshobson#8), batch concurrency semaphore (wshobson#9) - Relaxed flag/pennant detection thresholds (wshobson#12) - Price gap detection (wshobson#13), JSON NaN/Inf sanitization (wshobson#14) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Hi there,
This pull request shares a security update on maverick-mcp.
We also have an entry for maverick-mcp in our directory, MSeeP.ai, where we provide regular security and trust updates on your app.
We invite you to add our badge for your MCP server to your README to help your users learn from a third party that provides ongoing validation of maverick-mcp.
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MCP servers you can trust
Here are our latest evaluation results of maverick-mcp
Security Scan Results
Security Score: 100/100
Risk Level: low
Scan Date: 2025-08-26
Score starts at 100, deducts points for security issues, and adds points for security best practices
Security Findings
Low Severity Issues
This security assessment was conducted by MSeeP.ai, an independent security validation service for MCP servers. Visit our website to learn more about our security reviews.