No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by ruvnet · MCP Server · ★ 88
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is sublinear-time-solver safe to install? View the security audit →
🚀 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 sup
| Stars | 88 |
| Forks | 36 |
| Language | Rust |
| Category | MCP Server |
| License | MIT |
| Quality Score | 61.5100479123182/100 |
| Open Issues | 2 |
| Last Updated | 2026-08-02 |
| Created | 2025-09-19 |
| Platforms | cli, mcp, rust |
| Est. Tokens | ~29k |
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sublinear-time-solver is Rust + WASM sublinear-time solver for asymmetric diagonally dominant systems. Exposes Neumann series, push, and hybrid random-walk algorithms with npm/npx CLI and Flow-Nexus HTTP streaming for swarm c. It is categorized as a MCP Server with 88 GitHub stars.
sublinear-time-solver is primarily written in Rust. It covers topics such as asymmetric-matrices, conjugate-gradient-method, diagonally-dominant.
You can find installation instructions and usage details in the sublinear-time-solver GitHub repository at github.com/ruvnet/sublinear-time-solver. The project has 88 stars and 36 forks, indicating an active community.
sublinear-time-solver is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to sublinear-time-solver on Agent Skills Hub include MCP-Defender, toolhive-studio, mcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: