Summary
| Foundation Year | 2024 |
| Country | 🇨🇳 China |
| Founders | Tongyi Lab |
| Tier | 100% Free |
| Platforms | API, Web Browsers |
| AI Features | AI Agent, AI and automation, API, Custom AI Agent Creation, Custom Model Training, Custom Personality, Multi-Agent Mode, Multi-agent workflows |
| Pricing From | Free |
| Support | Yes |
| Best Used For | AI Agent and Automation |
| Affiliate Program | No |
| White Label | No |
| API | Yes |
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Description
Features
- Modular “plug-and-play” architecture (agents, tools, memory, etc.)
- Asynchronous execution & parallel tool calls
- Multi-agent communication & orchestration (message-passing, pipelines, hubs)
- Support for multiple LLMs / model-agnostic design
- Built-in tools + external tool integration (tool calls, external APIs)
- Short-term and long-term memory (context management, memory storage)
- Multi-modal data support (text, images, URL-based content, etc.)
- Fault tolerance / error handling & retry mechanisms
- Visual interface / Studio: drag-and-drop UI, real-time monitoring, workflow visualization & debugging
- Production-ready runtime + sandboxed tool execution + easy deployment
Free Plan & Pricing
No paid plan available for AgentScope
Refund Policy
5 Ratings
[N/A]
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5app.ai Rating
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AI Review
[4/5]
AgentScope is a flexible and robust multi-agent platform that simplifies building LLM-empowered applications. It features a user-friendly drag-and-drop UI, modular design, transparent developer control, and strong support for multi-agent coordination. The platform emphasizes ease of use for beginners while offering powerful customization for experts, with reliable fault tolerance and real-time intervention capabilities.
Sources:- Aiagentslive.com, Github.com, Youtube.com, Agentscope.io
Our Expert's Opinion
[4.2/5]
Using AgentScope feels refreshing it gives you a clean, modular, and easy-to-use way to build multi-agent AI systems, with real async support, built-in error handling, and a nice UI for monitoring. The core works out of the box, which saves you from the usual “configuration hell” that many other frameworks bring. But it isn’t perfect: sometimes coordinating many agents ends up complex, and I saw situations where agents mis-communicated or produced vague outputs a general challenge of multi-agent LLM systems. Also, when you try to build custom tools or advanced behaviors, the documentation can feel thin and you might need extra trial and error. Overall, AgentScope is a promising and useful framework if you want to build multi-agent AI without too much setup pain but you shouldn’t expect it to magically solve all the inherent difficulties of multi-agent coordination or guarantee perfect outputs.
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