agentscope-ai/agentscope

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Building block	What's inside
ReAct	Reasoning-acting loop with structured output, realtime interruption & resume, and batched (sequential / concurrent) tool acting
Toolkit	Agentic tool management over Python tools, MCP servers, and skills; ships with built-in coding tools (shell, file edit, search) and task/plan tools
Model	LLM, embedding, and TTS across major providers (OpenAI, Anthropic, Gemini, DashScope, DeepSeek, Moonshot, Volcengine, xAI, Ollama)
Context	Automatic compaction, tool-result offload, and context injection (system prompt, RAG, memory) via built-in middleware
Event System	Unified event bus streaming reasoning, tool calls, and multimodal content (text, image, audio) to the frontend
Permission & HITL	Fine-grained control over tools and resources, confirmation, bypass mode
Middleware	Composable hooks across the loop — reply, reasoning, acting, model calling, permission checking, context compression, system prompt
Memory	Agentic memory with switchable backends (ReMe, Mem0)
Workspace / Sandbox	Isolated tool & code execution — local, Docker, Apple Container, Bubblewrap, E2B, OpenSandbox, Daytona, K8s

Capability	What you get
Serving	Multi-tenancy, multi-session isolation, FastAPI backend, pre-built Web UI
Agent Team	Leader–worker orchestration, built-in team tools, task planning
Channels	Connect agents to IM platforms — Feishu (Lark), Discord, custom channels, message routing
RAG Service	Blob storage, index worker, multi-tenant retrieval
MCP & Skill Hub	Browse hubs (GitHub MCP Registry, ClawHub), install into your library, add to a workspace
Resource Sharing	Group- and org-level management for sharing models, MCP servers, skills, and workspaces
Persistence	SQL & NoSQL persistence of agent state and sessions
Scheduling	Scheduled tasks, agent wakeup, background task offloading

What is AgentScope 2.0?