Project screenshots
Overview
AgentScope 2.0 is a Python-based multi-agent framework that provides essential abstractions for building, running, and scaling LLM agents. It includes an SDK layer for composing agents from building blocks like ReAct loops, toolkits, and context management, alongside a batteries-included agent service featuring a FastAPI backend and pre-built Web UI for multi-tenant, multi-session applications.
Key features
- ReAct reasoning-acting loop with structured output and realtime interruption
- Agentic tool management over Python tools, MCP servers, and skills
- Automatic context compaction and tool-result offload via middleware
- Unified event bus streaming multimodal content
- Fine-grained permission control and Human-in-the-Loop (HITL)
- Agentic memory with switchable backends (ReMe, Mem0)
- Isolated workspace and sandbox execution (Docker, E2B, OpenSandbox, Daytona, K8s, etc.)
- Multi-tenancy and multi-session isolation with FastAPI backend
- Integration with GitHub MCP Registry and ClawHub
- Background task offloading and scheduled agent wakeup
Requirements, installation and quick start
Usage
Model compatibility and use cases
Supports LLM, embedding, and TTS across major providers including OpenAI, Anthropic, Gemini, DashScope, DeepSeek, Moonshot, xAI, and Ollama.
License and risk notes
Released under the Apache License 2.0.
Editorial verification 2026-08-09: repository URL, owner, description, license and repository statistics were reviewed. License metadata: Apache-2.0. README was fetched for the channel draft; re-check repository dependencies, releases and model terms before production use.
Release and maintenance
Recent updates include support for Feishu and Discord channels, MCP & Skill Hub integration, Daytona and K8s-based workspace/sandbox, ReMe long-term memory, Agentic Memory, and distributed, multi-tenancy RAG service.