cailculator-mcp 2.0.3

CAILculator MCP Server - High-dimensional data analysis with dual algebra frameworks

Applied Pathological Mathematics™ was born from this hypothesis:

Higher-dimensional algebras following the Cayley-Dickson sequence, which have been wrongly dismissed as "pathological" mathematics, can be interpreted and exploited for computational advantage, with particular benefits for data journalism, AGI research, and high-frequency quantitative analysis.

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CAILculator MCP Server v2.0

Universal High-Precision Mathematical Structure Analysis for AI Agents

"Leveling the playing field with high-end, formally verified data analysis tools"

🏆 Milestone: High-Precision Universal Engine (v2.0 - April 2026)

CAILculator has been completely overhauled to meet a $10^{-15}$ machine precision standard. The core engine is now strictly governed by Lean 4 formal verification, grounding every calculation in machine-verified mathematical truth.

• BilateralCollapse.lean: Formally proves the bilateral zero divisor identity ($PQ=0 \land QP=0$) used to gate all v2.0 transmissions.
• ChavezTransform_genuine.lean: Proved stability constant $M$, ensuring transform outputs never exceed rigorous theoretical bounds.
• Dual Frameworks: v2.0 natively supports both non-associative Cayley-Dickson and associative Clifford (Geometric) algebras.

The Mission: Data Analysis for Everyone

CAILculator v2.0 is designed to "level the playing field." By translating high-dimensional algebraic structures into domain-specific insights, we empower journalists, students, and researchers with tools previously reserved for elite quantitative shops.

Specialized Profiles

v2.0 introduces the Profile Manager, which projects universal algebraic patterns into semantic leads:

• Journalism Profile: Leveraging 30+ years of reporting expertise.
  • Tipping Points: Detects sudden structural collapses in budgets, consensus, or policy (Bilateral Zeros).
  • Sourcing Confidence: Measures signal robustness against noisy FOIA data (Transform Convergence).
  • Beats: Optimized mappers for Politics (Campaign Finance), Public Health, and Poverty.
• Quant Equity Profile: Designed for AGI-driven financial analysis.
  • Regime Detection: Bridges HMM statistical baselines with algebraic structural analysis.
  • Volatility Anchors: Identifies bifurcation risks using verified zero-divisor loci.
• RHI & General Data: Spectral research mapping (Riemann Hypothesis Investigation) and general-purpose CSV analysis.

Core v2.0 Upgrades

1. High-Precision standard ($10^{-15}$)

Unlike v1.x which relied on approximate $10^{-8}$ thresholds, v2.0 enforces full double-precision accuracy across all hypercomplex operations. If a pattern isn't a zero divisor to $10^{-15}$, it doesn't pass the v2.0 gate.

2. The "Option A" Embedding Fix

v2.0 resolves the "dispatch collapse" issue. Instead of embedding scalars into the $e_0$ channel, data is strictly mapped to non-real sedenion channels ($e_1$-$e_{15}$). This enables true mathematical differentiation across the Canonical Six patterns.

3. ZDTP 2.0 (Zero Divisor Transmission Protocol)

The protocol now uses Bilateral Grounding. Transmissions (16D → 32D → 64D) are derived from the four-factor bilateral interaction ${Px, xQ, Qx, xP}$, ensuring data integrity is verified by the same physics that governs the transform.

4. Cross-Algebra Universality

v2.0 identifies Pattern 2 as the "Universal Bilateral Anchor"—a zero divisor pattern that holds identically across both Cayley-Dickson and Clifford algebras.

System Requirements

• Python: 3.10 to 3.13 (64-bit)
• OS: Windows 10/11, macOS 10.15+, Linux (Ubuntu 20.04+)
• Architecture: 64-bit required for high-precision scipy and numpy operations.

Installation

pip install cailculator_mcp

Configuration (Claude Desktop)

Open your configuration file and add the CAILculator server:

{
  "mcpServers": {
    "cailculator": {
      "command": "cailculator-mcp",
      "args": ["--transport", "stdio"],
      "env": {
        "CAILCULATOR_API_KEY": "your_api_key_here"
      }
    }
  }
}

Available Tools (v2.0)

🔬 High-Precision Tools

• chavez_transform: Apply the formally verified transform to find hidden structure in data.
• detect_patterns: Algebraic detection of Tipping Points and Pattern Consistency.
• verify_bilateral_oracle: High-precision check ($10^{-15}$) for any zero divisor pair.
• map_e8_orbit: Project 16D/32D vectors onto verified E8 Weyl orbits.

📰 Domain Intelligence

• list_domain_profiles: Explore Journalism, Quant, and RHI tiers.
• zdtp_transmit: Protocol-level structural data transmission with convergence scoring.
• illustrate: High-precision visualizations (Refactored to resolve System32 path regressions).

📈 Financial & Batch Analysis

• regime_detection: Dual-method market analysis.
• batch_analyze_market: Smart sampling strategy for GB-scale datasets.

Research & Collaboration

Built on formal research published at DOI: 10.5281/zenodo.17402495. All core structural claims are verified in Lean 4.

Interested in custom profile development? Contact Chavez AI Labs at [e-mail] or [e-mail].

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Chavez AI Labs - "Verification over assumption. Better math, less suffering."