<img src="https://github.com/alibaba/spring-ai-alibaba/raw/v2.0.0-M1.1/docs/imgs/architecture-new.png" alt="architecture" style="max-width: 740px; height: auto" />
Spring AI Alibaba Admin is a one-stop Agent platform that supports visualized Agent development, observability, evaluation, and MCP management, etc. It also integrates with open-source low-code platforms like Dify, enabling rapid migration from DSL to Spring AI Alibaba project.
Spring AI Alibaba Agent Framework is an agent development framework that can quickly develop agents with builtin Context Engineering and Human In The Loop support. For scenarios requiring more complex process control, Agent Framework offers built-in workflows like SequentialAgent, ParallelAgent, RoutingAgent, LoopAgent and SupervisorAgent.
Spring AI Alibaba Graph serves as the underlying runtime of the Agent Framework, providing essential capabilities such as persistence, workflow orchestration, and streaming required for long-running stateful agents. Compared to the Agent Framework, users can build more flexible multi-agent workflows based on the Graph API.
Multi-Agent Orchestration: Compose multiple agents with built-in patterns including SequentialAgent, ParallelAgent, LlmRoutingAgent, and LoopAgent for complex task execution.
Context Engineering: Built-in best practices for context engineering policies to improve agent reliability and performance, including human-in-the-loop, context compaction, context editing, model & tool call limit, tool retry, planning, dynamic tool selection.
Graph-based Workflow: Graph based workflow runtime and api for conditional routing, nested graphs, parallel execution, and state management. Export workflows to PlantUML and Mermaid formats.
A2A Support: Agent-to-Agent communication support with Nacos integration, enabling distributed agent coordination and collaboration across services.
Rich Model, Tool and MCP Support: Leveraging core concepts of Spring AI, supports multiple LLM providers (DashScope, OpenAI, etc.), tool calling, and Model Context Protocol (MCP).
One-stop Agent Platform: Build agent in a visualized way, deploy agent without code or export as a standalone java project.

There's a ChatBot example provided by the community at examples/chatbot.
Download the code.
shell
git clone --depth=1 https://github.com/alibaba/spring-ai-alibaba.git
cd spring-ai-alibaba/examples/chatbot
Start the ChatBot.
Before starting, set API-KEY first (visit Aliyun Bailian to get API-KEY): ```shell
export AI_DASHSCOPE_API_KEY=your-api-key ```
shell
mvn spring-boot:run
Chat with ChatBot.
Open the browser and visit http://localhost:8080/chatui/index.html to chat with the ChatBot.

Add dependencies
```xml com.alibaba.cloud.ai spring-ai-alibaba-agent-framework 1.1.2.0
com.alibaba.cloud.ai spring-ai-alibaba-starter-dashscope 1.1.2.1 ```
Define Chatbot
For more details of how to write a Chatbot, please check the Quick Start on our official website.
This project consists of several core components:
| Repository | Description | ⭐ |
|---|---|---|
| Spring AI Alibaba Graph | A low-level orchestration framework and runtime for building, managing, and deploying long-running, stateful agents. | |
| Spring AI Alibaba Admin | Local visualization toolkit for the development of agent applications, supporting project management, runtime visualization, tracing, and agent evaluation. | |
| Spring AI Extensions | Extended implementations for Spring AI core concepts, including DashScopeChatModel, MCP registry, etc. | |
| Spring AI Alibaba Examples | Spring AI Alibaba Examples. | |
| JManus | A Java implementation of Manus built with Spring AI Alibaba, currently used in many applications within Alibaba Group. | |
| DataAgent | A natural language to SQL project based on Spring AI Alibaba, enabling you to query databases directly with natural language without writing complex SQL. | |
| DeepResearch | Deep Research implemented based on spring-ai-alibaba-graph. |
130240015687 and join.
Made with ❤️ by the Spring AI Alibaba Team
$ claude mcp add spring-ai-alibaba \
-- python -m otcore.mcp_server <graph>