by agentscope-ai · MCP Server · ★ 35.4k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
pip install agentscope
uv pip install agentscope
Taken from the project's README on GitHub. Check the security audit before running it.
Flagged: environment access. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
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 | 35,375 |
| Forks | 3,784 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 70/100 |
| Open Issues | 727 |
| Last Updated | 2026-11-04 |
| Created | 2024-01-12 |
| Platforms | mcp, python |
| Est. Tokens | ~18k |
中文主页 FAQ <img src="https://img.shields.io/badge/Docs-English%7C%
These tools work well together with agentscope for enhanced workflows:
Looking for a agentscope alternative? If you're comparing agentscope 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.
AI Agent Assistant & development framework that integrates lots of IM platforms, LLMs, plugins and AI feature,
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with
A generative speech model for daily dialogue.
📦 Repomix is a powerful tool that packs your entire repository into a single, AI-friendly file. Perfect for w
🔥 MaxKB is an open-source platform for building enterprise-grade agents. 强大易用的开源企业级智能体平台。
Pocket Flow: Codebase to Tutorial
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: