China just released a Python framework for building Ai Agent 100% open source
Alibaba just launched AgentScope: an open-source Python framework for building truly intelligent AI agents. Go beyond chatbots; design collaborative, reasoning AI systems today!

China Just Released an Open-Source Python Framework for Building AI Agents and It's the Real Deal
If you've been frustrated by AI agent frameworks that promise the world and deliver a glorified chatbot builder, AgentScope might be worth your attention.
Released by Alibaba's DAMO Academy — the same research lab behind the Qwen language models — AgentScope is a full Agent-Oriented Programming framework built from the ground up around how agents actually think, remember, and collaborate. It's 100% open source under the Apache 2.0 license.
What Makes It Different
Most frameworks hand you building blocks and leave you to figure out the architecture. AgentScope ships with the architecture already thought through. Visual agent design, MCP tool support, memory, RAG pipelines, and reasoning modules all come built in — and they're designed to work together, not bolted on as afterthoughts.
The visual agent builder lets you map out your entire system before writing a single line of code. Once you have the structure, you wire in your tools using native MCP support, which means any external tool can plug directly into any agent in your pipeline. Each agent gets its own memory layer, so context, decisions, and history persist across sessions without you having to manage state manually.
The RAG pipeline connects to your own documents, databases, and knowledge bases. The reasoning modules let agents plan, reflect, and self-correct — no human in the loop required for every decision.
How It Actually Works
You define a goal. AgentScope maps out the agent roles needed to accomplish it. Each agent receives its tools, memory, and reasoning layer. They coordinate, pass results between each other, and the final output surfaces at the end.
A single complex task might route through a planner agent, a researcher agent, a coder agent, and a critic agent — each doing its specific job — before converging into one clean deliverable. That's multi-agent coordination that functions as a system, not a pile of isolated API calls stitched together with duct tape.
Who Built It and Why It Matters
DAMO Academy didn't assemble AgentScope from existing pieces. According to the project, the framework was designed from first principles around agent-oriented thinking. The community has already started extending it into data pipelines, research workflows, and automation systems the original team never planned for — which is usually a good sign that the underlying design is solid.
The Apache 2.0 license means you can use it commercially, modify it, and distribute it freely.
https://github.com/agentscope-ai/agentscope
If you're building anything serious with AI agents, it's worth an afternoon to dig in.


