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AgentScope

Open-source multi-agent platform from Alibaba's DAMO Academy for building LLM agents with visual workflows and runtime management.

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In Plain English

Open-source multi-agent platform from Alibaba's DAMO Academy for building LLM agents with visual workflows and runtime management.

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Overview

AgentScope is an open-source multi-agent framework originally developed inside Alibaba's DAMO Academy and now broadly maintained by the agentscope-ai organisation. It pairs a Python SDK with a browser-based Studio so teams can prototype agent applications either by writing code or by dragging nodes onto a canvas, then promote the same flow into a managed runtime. The framework leans heavily into the multi-agent case: actor-style message passing, pipelines, group chats, dynamic routing, and built-in tools for memory, retrieval, code execution and computer use. A 'Spark' design system gives every agent a coherent UI for chat, tool calls and reasoning traces, which dramatically shortens the path from prototype to a stakeholder-ready demo. Production features include observability hooks, distributed agent orchestration across nodes, fault-tolerant message replay and a model adapter layer that supports OpenAI, Anthropic, Qwen, DeepSeek and local engines like vLLM. AgentScope is one of the most popular agent frameworks coming out of the Chinese AI ecosystem in 2026, sitting alongside LangGraph and CrewAI as a serious option for teams that want a single repo covering the full prototype-to-production journey. It is MIT-licensed and ships an MCP-compatible tool layer so agents can call any MCP server natively.

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Key Features

Feature information is available on the official website.

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Pricing Plans

Open Source

$0

    Studio Cloud

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      Best Use Cases

      🎯

      Research teams prototyping novel multi-agent architectures

      ⚡

      Engineers shipping production agents that need distributed orchestration

      🔧

      Teams wanting a visual builder backed by a real Python framework

      🚀

      Apps that need to combine LLM tool-use with computer-use

      Pros & Cons

      ✓ Pros

      • ✓Same primitives in the SDK and the visual Studio — no rewrite when going from prototype to production
      • ✓Distributed runtime is a genuine differentiator vs single-process frameworks
      • ✓Native MCP client means existing MCP servers plug in with no glue code
      • ✓MIT/Apache licensing makes it safe for commercial and on-prem deployment

      ✗ Cons

      • ✗Studio Cloud is still beta — managed hosting is not yet a turnkey option
      • ✗English documentation trails the Chinese-language docs in spots
      • ✗Smaller third-party ecosystem than LangGraph or CrewAI
      • ✗Distributed runtime adds operational complexity teams may not need for small agents

      Frequently Asked Questions

      How much does AgentScope cost?+

      AgentScope pricing starts at $0. They offer 2 pricing tiers.
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      Quick Info

      Category

      AI Agents

      Website

      agentscope.io
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