Micro-Agent: A lightweight AI agent framework for vertical domain applications | 面向垂域应用的轻量级 AI Agent 框架

by fdueblab · MCP Server · ★ 101

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install Micro-Agent

git clone https://github.com/fdueblab/Micro-Agent.git

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 69/100

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.

ai-agentfastapilitellmllmmcpragreact-agentvertical-domain

Quick Facts

Stars101
Forks17
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score69/100
Open Issues4
Last Updated2026-09-30
Created2025-03-25
Platformsmcp, python
Est. Tokens~14k

About Micro-Agent

为什么选择 Micro-Agent 如果你需要为特定行业快速构建一个专业 Agent 并以 API 服务形式交付,Micro-Agent 是最短路径。 各框架定位: Micro-Agent 面向垂域专业 Agent 服务交付 · LangGraph 面向复杂多步工作流编排 · AutoGen 面向多角色智能体协作 · OpenClaw 面向个人效率自动化 架构 核心组件: LLM Layer — 通过 litellm 统一接口,一套代码切换 OpenAI / DeepSeek / Claude / Ollama 等任意模型 Agent Core — ReAct 执行引擎(Think → Act → Observe 循环),支持 SubAgent 子任务分发与 REPL 沙箱执行 Memory — 会话记忆系统,支持短期记忆、文件持久化、跨会话恢复 Skills —...

Micro-Agent alternative? Top 6 similar tools

Looking for a Micro-Agent alternative? If you're comparing Micro-Agent 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.

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    Production-ready multi-agent orchestration engine built on Google ADK. Database-driven agent config, 50+ LLM p

  • edgecrab by raphaelmansuy · ⭐ 93

    EdgeCrab 🦀 A Super Powerful Personal Assistant inspired by NousHermes and OpenClaw — Rust-native, blazing-fas

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How this security grade is produced

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:

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