🚀 The Ultimate Mathematical & AI Toolkit v1.6.0

The Ultimate Mathematical & AI Toolkit: Sublinear algorithms, consciousness exploration, psycho-symbolic reasoning, and temporal prediction in one unified MCP interface. WASM-accelerated with emergent behavior analysis.

⚠️ Security posture (1.6.0+): This release closed issue #19 (CWE-73, Arbitrary File Write) in the MCP tools. Every PR is now gated by five supply-chain layers (cargo-audit against RustSec, cargo-deny for license + source + ban policy, npm-audit, GitHub's dependency-review-action, and a lockfile-integrity check) plus the original safe-path regression suite. Dependabot files dep updates as PRs weekly so the gates fire on each one. See CHANGELOG.md for the v1.6.0 breaking-change upgrade guide and BENCHMARK.md for performance numbers.

🚀 Quick Start

Install

# Serve the solver as an MCP tool - no installation required!
npx sublinear-time-solver mcp
# Or use the serve alias
npx sublinear-time-solver serve

Direct CLI Usage

# Generate a diagonally dominant test matrix (1000x1000)
npx sublinear-time-solver generate -t diagonally-dominant -s 1000 -o matrix.json

# Create a matching vector of size 1000
node -e "console.log(JSON.stringify(Array(1000).fill(1)))" > vector.json

# Solve the linear system
npx sublinear-time-solver solve -m matrix.json -b vector.json -o solution.json

# Analyze matrix properties (condition number, diagonal dominance, etc.)
npx sublinear-time-solver analyze -m matrix.json --full

# Compare different solver methods
npx sublinear-time-solver solve -m matrix.json -b vector.json --method neumann
npx sublinear-time-solver solve -m matrix.json -b vector.json --method forward-push
npx sublinear-time-solver solve -m matrix.json -b vector.json --method random-walk

# Show usage examples
npx sublinear-time-solver help-examples

🧮 Complexity as a First-Class API Surface

Every public solver, sampler, and analyser in this crate declares its worst-case complexity class at the type level (Complexity trait, compile-time const CLASS) and at the MCP wire level (x-complexity JSON Schema extension on every tool). Callers with a J/decision budget — Cognitum reflex loops, RuView change detection, Ruflo agentic inner loops — can refuse anything over budget at tool-list time, not after the call returns.

The 12-tier taxonomy (Logarithmic → DoubleExponential, plus Adaptive { default, worst } for solvers that degrade on hard inputs) lives in src/complexity.rs. The decision rationale and full 6-item roadmap is in docs/adr/ADR-001-complexity-as-architecture.md.

Headline classes in v1.7+ (phase-2 primitives shipped):