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 raphaelmansuy · MCP Server · ★ 80
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is edgecrab safe to install? View the security audit →
EdgeCrab 🦀 "Your SuperAgent — built in Rust." EdgeCrab is a SuperAgent — a personal assistant and coding agent forged in Rust. It carries the soul of Nous Hermes Agent (autonomous reasoning, persistent memory, user-first alignment) and the always-on presence of OpenClaw (17 messaging gateways, smart-home integration), packaged as a stripped native release binary of about 49 MB on current macOS arm64 builds, with zero Python or Node.js runtime dependencies. Runs on Linux, macOS, and Android (Termux). Latest release: v0.10.0 — Hermes-parity terminal UX: live activity shelf with tool-progress tails, delegation dashboard (kil
| Stars | 80 |
| Forks | 16 |
| Language | Rust |
| Category | MCP Server |
| Quality Score | 61.3021316269559/100 |
| Open Issues | 5 |
| Last Updated | 2026-07-24 |
| Created | 2026-04-05 |
| Platforms | cli, mcp, rust |
| Est. Tokens | ~34k |
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edgecrab is EdgeCrab 🦀 A Super Powerful Personal Assistant inspired by NousHermes and OpenClaw — Rust-native, blazing-fast terminal UI, ReAct tool loop, multi-provider LLM support, ACP protocol, gateway adapters. It is categorized as a MCP Server with 80 GitHub stars.
edgecrab is primarily written in Rust. It covers topics such as agentic-ai, ai-agent, autonomous-agent.
You can find installation instructions and usage details in the edgecrab GitHub repository at github.com/raphaelmansuy/edgecrab. The project has 80 stars and 16 forks, indicating an active community.
The top alternatives to edgecrab on Agent Skills Hub include zeph, toktrack, blade-code. 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: