agentscope
AgentScope: A Flexible yet Robust Multi-Agent Platform.
Decision gist · record as of 2026-08-14
Yes. AgentScope is actively maintained, well-documented, and designed for production use. It offers a comprehensive toolkit for multi-agent systems with low install friction and permissive licensing. The 25 runtime dependencies are substantial but necessary for the breadth of features (LLM APIs, observability, async I/O, code parsing). Install if you are building agents that need tool use, multi-agent coordination, or service deployment; skip if you need only simple LLM chat.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.11 or higher; LLM API credentials (e.g., DashScope, OpenAI, Anthropic) needed to run agents.
- Low friction installation; pure Python wheel.
- Active maintenance with recent release (7 days old) and strong community signal (28949 GitHub stars).
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial use, modification, and distribution with minimal restrictions—suitable for production deployment.
last release 2026-08-07 (7 days) · last repo commit 2026-08-14 · 28,949 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 251,711 downloads/mo, #8,568 on PyPI
Alternatives
Verify before relying
pip install agentscope
from agentscope.agent import Agent
from agentscope.model import DashScopeChatModel
from agentscope.credential import DashScopeCredential
from agentscope.message import UserMsg
agent = Agent(
name="Assistant",
model=DashScopeChatModel(
credential=DashScopeCredential(api_key="..."),
model="qwen3.6-plus"
)
)
await agent.reply_stream(UserMsg("user", "Hello"))- Performance characteristics and latency for multi-agent orchestration at scale.
- Compatibility and integration depth with specific LLM providers beyond those documented.
- Production deployment guidance for high-concurrency multi-tenant scenarios.
What it is and what it does
AgentScope is a framework for building and deploying multi-agent systems powered by large language models. It provides composable building blocks—agents with reasoning-acting loops, tool management (Python tools, MCP servers, skills), model integration across major providers, context management with automatic compaction, and an event system for streaming reasoning and tool calls. The framework is designed to work with increasingly capable agentic LLMs, leveraging their reasoning and tool-use abilities rather than constraining them with rigid orchestration.
Beyond the SDK layer, AgentScope includes a batteries-included agent service—a FastAPI backend with a pre-built Web UI—that turns agents into multi-tenant, multi-session applications. It supports agent teams with leader-worker orchestration, channels for connecting to messaging platforms (Feishu, Discord), RAG services, and a hub system for discovering and installing MCP servers and skills. The framework also provides isolated execution environments (local, Docker, K8s, E2B, Daytona) for safe tool and code execution.
Use it for
- Build a reasoning agent that breaks down tasks, calls tools (shell, file edit, search), and streams results to a frontend.
- Deploy a multi-agent team service where specialized agents coordinate on complex tasks with leader-worker orchestration.
- Connect agents to messaging platforms (Feishu, Discord) to answer questions and execute tasks from chat channels.
- Implement RAG-augmented agents that retrieve and reason over documents in a multi-tenant service.
- Compose agents with long-term memory (ReMe, Mem0) to maintain context across sessions.
- Integrate with multiple LLM providers (OpenAI, Anthropic, DashScope, DeepSeek) without rewriting agent logic.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
AgentScope is actively maintained, well-documented, and designed for production use. It offers a comprehensive toolkit for multi-agent systems with low install friction and permissive licensing. The 25 runtime dependencies are substantial but necessary for the breadth of features (LLM APIs, observability, async I/O, code parsing). Install if you are building agents that need tool use, multi-agent coordination, or service deployment; skip if you need only simple LLM chat.
Install
agentscope on PyPI
Before you install
Low friction installation; pure Python wheel. Active maintenance with recent release (7 days old) and strong community signal (28949 GitHub stars). Requires Python 3.11 or higher.
Requires Python 3.11 or higher; LLM API credentials (e.g., DashScope, OpenAI, Anthropic) needed to run agents.
License in practice
Apache-2.0 permissive license allows commercial use, modification, and distribution with minimal restrictions—suitable for production deployment.
Quickstart
pip install agentscope
from agentscope.agent import Agent
from agentscope.model import DashScopeChatModel
from agentscope.credential import DashScopeCredential
from agentscope.message import UserMsg
agent = Agent(
name="Assistant",
model=DashScopeChatModel(
credential=DashScopeCredential(api_key="..."),
model="qwen3.6-plus"
)
)
await agent.reply_stream(UserMsg("user", "Hello"))Verify before relying
- Performance characteristics and latency for multi-agent orchestration at scale.
- Compatibility and integration depth with specific LLM providers beyond those documented.
- Production deployment guidance for high-concurrency multi-tenant scenarios.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.11 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 25 packagesaioitertoolsanthropicdashscopedocstring_parserfiletypejson5json_repairmcphttpxnumpyopenaipython-datauriopentelemetry-apiopentelemetry-sdkopentelemetry-exporter-otlpopentelemetry-semantic-conventionspython-socketioshortuuidpython-frontmatterjinja2aiofilestree_sittertree_sitter_bashjsonschematzdata |
| Maintenance | Actively maintained 7 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 251,711 / month, #8,568 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersIntended Audience :: Science/ResearchOperating System :: OS IndependentProgramming Language :: Python :: 3Programming Language :: Python :: 3.11Topic :: Scientific/Engineering :: Artificial Intelligence |
Evidence: agentscope-2.0.6-py3-none-any.whl
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