AgentScope
Alibaba Tongyi Lab's open-source framework for multi-agent applications
Overview
AgentScope is an open-source (Apache-2.0) multi-agent framework from Alibaba's Tongyi Lab. Version 2.0 (May 2026) adds an agent service with web UI, multi-tenancy, agent teams, RAG, an MCP and skill hub, sandboxes from Docker to Kubernetes and realtime voice agents, with Python, Java, TypeScript and Go SDKs and support for most major model providers.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 12 Oct 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.
What you can produce with AgentScope
- Multi-agent framework with leader-and-worker agent teams
- Agent service with FastAPI backend, web UI and multi-tenancy
- Code sandboxes from local and Docker to E2B, Daytona and Kubernetes
- RAG service, MCP and skill hub, and memory via ReMe or Mem0
- Realtime voice agents and A2A support
- Python, Java, TypeScript and Go SDKs
AgentScope 2.0 is one of the most complete open multi-agent stacks: an agent service with web UI and multi-tenancy, agent teams, RAG, MCP, many sandbox backends and realtime voice, all model-agnostic and Apache-licensed.
The breadth comes with churn. The API changes quickly, the non-Python SDKs are at different stages, and there is no managed hosting. Best for teams that want a full stack, especially those already on Qwen or Alibaba Cloud.
What we found
AgentScope is an open-source framework for building multi-agent applications from the SysML team at Alibaba's Tongyi Lab. Its first release went out in February 2024 with an accompanying paper, version 1.0 followed in August 2025, and version 2.0 shipped on 25 May 2026, with 2.0.9 the latest release at the end of September. The project has moved from the ModelScope GitHub organisation to its own, agentscope-ai, and is licensed under Apache 2.0. Documentation is in English and Chinese.
Version 2.0 is a substantial expansion. The separate AgentScope Runtime has been folded in, and the framework now ships an agent service built on FastAPI with a ready-made web interface, multi-tenant and multi-session isolation, leader-and-worker agent teams, a RAG service, an MCP and skill hub, scheduling and SQL or NoSQL persistence. Agents can run code in sandboxes ranging from local and Docker to Apple Container, Bubblewrap, E2B, OpenSandbox, Daytona and Kubernetes. Recent additions include A2A agents, realtime voice agents across several providers, standard operating procedures, model-routing middleware and WebRTC voice. Channels connect agents to Feishu, Discord and DingTalk.
It is model-agnostic, supporting OpenAI, Anthropic, Gemini, Alibaba's DashScope, DeepSeek, Moonshot, Volcengine, xAI, MiniMax and local models through Ollama, with ReMe and Mem0 for memory. Python is the main SDK, and there are Java, TypeScript and Go versions at different stages; the Java SDK is on its own 2.0 line. Around it sit related projects for memory, evaluation, reinforcement fine-tuning, a visual studio and a personal assistant app.
There is nothing to buy: the framework is free to self-host, and we found no managed cloud version. Its strengths are breadth and Alibaba's backing; the trade-offs are a fast-changing API and documentation that trails the code. AgentScope suits teams, particularly those already using Qwen or Alibaba Cloud, who want a full multi-agent stack rather than a thin library.
Compiled by RECATOOLS from public sources: vendor documentation and pricing, code repositories and published reporting.
About this listing
This entry was compiled from publicly available data including AgentScope's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with AgentScope unless explicitly stated.
Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.
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