by rootflo · MCP Server · ★ 203
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 203 |
| Forks | 36 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 56/100 |
| Open Issues | 28 |
| Last Updated | 2026-11-06 |
| Created | 2024-07-25 |
| Platforms | mcp, python |
| Est. Tokens | ~15k |
Enterprise AI Middleware For Building Production Ready AI Applications Open source alternative to UnifyApps, LyzrAI, SuperAGI & AgentGPT Alternative to n8n, for building enterprise grade AI workflows GitHub • Website • Docu
These tools work well together with wavefront for enhanced workflows:
Looking for a wavefront alternative? If you're comparing wavefront with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
An introduction to the world of AI Agents
Save thousands of lines of code by building universal, domain-agnostic Multi-Agent Systems (MAS) through high-
This repository contains hands-on projects, code examples, and deployment workflows. Explore multi-agent syste
Harness the power of local LLMs with this TUI MCP Client for Ollama. Featuring all core MCP primitives (tools,
RAGLight is a modular framework for Retrieval-Augmented Generation (RAG). It makes it easy to plug in differen
CoexistAI is a modular, developer-friendly research assistant framework . It enables you to build, search, sum
Explore other popular mcp server tools:
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: