AI Skill Hub 强烈推荐:AgentScope智能体框架 是一款优质的AI工具。在 GitHub 上收获超过 25.1k 颗 Star,AI 综合评分 8.6 分,在同类工具中表现稳健。如果你正在寻找可靠的AI工具解决方案,这是一个值得深入了解的选择。
AgentScope智能体框架 是一款基于 Python 开发的开源工具,专注于 多智能体、可视化、MCP协议 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。
AgentScope智能体框架 是一款基于 Python 开发的开源工具,专注于 多智能体、可视化、MCP协议 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。
# 方式一:pip 安装(推荐)
pip install agentscope
# 方式二:虚拟环境安装(推荐生产环境)
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install agentscope
# 方式三:从源码安装(获取最新功能)
git clone https://github.com/agentscope-ai/agentscope
cd agentscope
pip install -e .
# 验证安装
python -c "import agentscope; print('安装成功')"
# 命令行使用
agentscope --help
# 基本用法
agentscope input_file -o output_file
# Python 代码中调用
import agentscope
# 示例
result = agentscope.process("input")
print(result)
# agentscope 配置文件示例(config.yml) app: name: "agentscope" debug: false log_level: "INFO" # 运行时指定配置文件 agentscope --config config.yml # 或通过环境变量配置 export AGENTSCOPE_API_KEY="your-key" export AGENTSCOPE_OUTPUT_DIR="./output"
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中文主页 | Tutorial | Roadmap (Jan 2026 -) | FAQ
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<p align="center"> <a href="https://arxiv.org/abs/2402.14034"> <img src="https://img.shields.io/badge/cs.MA-2402.14034-B31C1C?logo=arxiv&logoColor=B31C1C" alt="arxiv" /> </a> <a href="https://pypi.org/project/agentscope/"> <img src="https://img.shields.io/badge/python-3.10+-blue?logo=python" alt="pypi" /> </a> <a href="https://pypi.org/project/agentscope/"> <img src="https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fpypi.org%2Fpypi%2Fagentscope%2Fjson&query=%24.info.version&prefix=v&logo=pypi&label=version" alt="pypi" /> </a> <a href="https://discord.gg/eYMpfnkG8h"> <img src="https://img.shields.io/discord/1194846673529213039?label=Discord&logo=discord" alt="discord" /> </a> <a href="https://doc.agentscope.io/"> <img src="https://img.shields.io/badge/Docs-English%7C%E4%B8%AD%E6%96%87-blue?logo=markdown" alt="docs" /> </a> <a href="./LICENSE"> <img src="https://img.shields.io/badge/license-Apache--2.0-black" alt="license" /> </a> </p>
<p align="center"> <img src="https://trendshift.io/api/badge/repositories/20310" alt="agentscope-ai%2Fagentscope | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/> </p>
AgentScope requires Python 3.10 or higher.
pip install agentscope
Or with uv:
uv pip install agentscope
```bash
cd agentscope
pip install -e .
```
Use individual MCP tools as local callable functions to compose toolkits or wrap into a more complex tool.
from agentscope.mcp import HttpStatelessClient
from agentscope.tool import Toolkit
import os
async def fine_grained_mcp_control():
# Initialize the MCP client
client = HttpStatelessClient(
name="gaode_mcp",
transport="streamable_http",
url=f"https://mcp.amap.com/mcp?key={os.environ['GAODE_API_KEY']}",
)
# Obtain the MCP tool as a **local callable function**, and use it anywhere
func = await client.get_callable_function(func_name="maps_geo")
# Option 1: Call directly
await func(address="Tiananmen Square", city="Beijing")
# Option 2: Pass to agent as a tool
toolkit = Toolkit()
toolkit.register_tool_function(func)
# ...
# Option 3: Wrap into a more complex tool
# ...
AgentScope provides `MsgHub` and pipelines to streamline multi-agent conversations, offering efficient message routing and seamless information sharing
from agentscope.pipeline import MsgHub, sequential_pipeline
from agentscope.message import Msg
import asyncio
async def multi_agent_conversation():
# Create agents
agent1 = ...
agent2 = ...
agent3 = ...
agent4 = ...
# Create a message hub to manage multi-agent conversation
async with MsgHub(
participants=[agent1, agent2, agent3],
announcement=Msg("Host", "Introduce yourselves.", "assistant")
) as hub:
# Speak in a sequential manner
await sequential_pipeline([agent1, agent2, agent3])
# Dynamic manage the participants
hub.add(agent4)
hub.delete(agent3)
await hub.broadcast(Msg("Host", "Goodbye!", "assistant"))
asyncio.run(multi_agent_conversation())
高质量多智能体框架,MCP支持增强互操作性,活跃维护和大社区支持。可视化设计降低使用门槛,是企业级智能体开发首选。
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ Apache 2.0 — 宽松开源协议,可商用,需保留版权声明和 NOTICE 文件,含专利授权条款。
总体来看,AgentScope智能体框架 是一款质量优秀的AI工具,在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态,建议收藏备用,结合自身场景选择合适时机引入使用。
| 原始名称 | agentscope |
| 原始描述 | 开源MCP工具:Build and run agents you can see, understand and trust.。⭐25.1k · Python |
| Topics | 多智能体可视化MCP协议LLM应用开源框架 |
| GitHub | https://github.com/agentscope-ai/agentscope |
| License | Apache-2.0 |
| 语言 | Python |
收录时间:2026-05-14 · 更新时间:2026-05-16 · License:Apache-2.0 · AI Skill Hub 不对第三方内容的准确性作法律背书。