agentscope

Build and run agents you can see, understand and trust.

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Install / Use

claude mcp add agentscope-ai -- npx -y github:agentscope-ai/agentscope

If the server publishes to npm under a different name, use that package instead — check the repo README.

About this skill

🔌

MCP Server

Model Context Protocol server

Quality Score

92/100

Skill content

View source on GitHub

中文主页 | Documentation | Roadmap

What is AgentScope 2.0?

AgentScope 2.0 is a production-ready, easy-to-use agent framework with essential abstractions that keep up with rising model capability.

We design for increasingly agentic LLMs. Our approach leverages the models' reasoning and tool use abilities rather than constraining them with strict prompts and opinionated orchestrations.

News

[2026-08] INTE: Feishu (Lark) and Discord channels supported. Feishu | Discord
[2026-08] FEAT: Channels supported — connect agents to IM platforms in agent service. Example | Docs
[2026-08] INTE: GitHub MCP Registry and ClawHub supported as built-in hubs. Example | Docs
[2026-08] FEAT: MCP & Skill Hub supported — browse a hub, install into your library, add to a workspace. Example | Docs
[2026-07] INTE: Daytona-based workspace/sandbox supported. Docs
[2026-07] INTE: K8s, OpenSandbox-based workspace/sandbox supported. Docs
[2026-07] INTE: ReMe long-term memory supported. Example | Docs
[2026-06] FEAT: Agentic Memory supported. Example | Docs
[2026-06] FEAT: Distributed & Multi-Tenancy & Multi-Session RAG service supported. Docs
[2026-06] FEAT: RAG supported. Example | Docs

More news →

Community

Welcome to join our community on

| Discord | DingTalk | |----------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------| | <img src="https://gw.alicdn.com/imgextra/i1/O1CN01hhD1mu1Dd3BWVUvxN_!!6000000000238-2-tps-400-400.png" width="100" height="100"> | <img src="./assets/images/dingtalk_qr_code.png" width="100" height="100"> |

Quickstart

Installation

AgentScope requires Python 3.11 or higher.

From PyPI

uv pip install agentscope

From source

# Pull the source code from GitHub
git clone -b main https://github.com/agentscope-ai/agentscope.git

# Install the package in editable mode
cd agentscope

uv pip install -e .

Agent

The SDK layer — compose an agent from a rich set of building blocks:

| 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, 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 |

Start your first agent with AgentScope 2.0:

from agentscope.agent import Agent
from agentscope.tool import Toolkit, Bash, Grep, Glob, Read, Write, Edit
from agentscope.credential import DashScopeCredential
from agentscope.model import DashScopeChatModel
from agentscope.message import UserMsg
from agentscope.event import EventType

import os, asyncio


async def main() -> None:
    agent = Agent(
        name="Friday",
        system_prompt="You're a helpful assistant named Friday.",
        model=DashScopeChatModel(
            credential=DashScopeCredential(
              api_key=os.environ["DASHSCOPE_API_KEY"]
            ),
            model="qwen3.6-plus",
        ),
        toolkit=Toolkit(
            tools=[
                Bash(),
                Grep(),
                Glob(),
                Read(),
                Write(),
                Edit(),
            ]
        ),
    )

    async for evt in agent.reply_stream(UserMsg("Tony", "Hi, Friday!")):
        # Handle the event stream, e.g., print the message, update UI, etc.
        match evt.type:
            case EventType.REPLY_START:
                ...
            case EventType.MODEL_CALL_START:
                ...
            case EventType.TEXT_BLOCK_START:
                ...
            case EventType.TEXT_BLOCK_DELTA:
                ...
            case EventType.TEXT_BLOCK_END:
                ...

            # Handle other event types

asyncio.run(main())

Agent Service — All You Need to Build Your App

AgentScope ships a batteries-included agent service — a FastAPI backend with a pre-built Web UI (examples/web_ui) that turns your agents into a multi-tenant, multi-session application, with rich capabilities out of the box:

| 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 |

Everything above is composable, so you can assemble your own application on top of the service with minimal glue code.

Truncated for display — read the full file on GitHub.

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agentscope-ai

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View on GitHub

GitHub Stars32.1k

CategoryAI

Updated14h ago

Forks3.5k

agentscope-ai/agentscope

Languages

Python

Security Score

95/100

Audited on Sep 21, 2026

1 low