LightAgent
ActiveDescription
Lightweight AI agent framework with built-in memory, tool calling, and tree-of-thought reasoning, supporting multi-agent collaboration and self-learning, compatible with OpenAI, DeepSeek, Qwen, and other major LLMs with MCP/SSE protocol integration.
Key Features
- Ultra-Lightweight Framework: No LangChain/LlamaIndex dependencies, core framework stays small and modular, ready in 5 minutes
- Native Skill System: Create reusable skill modules with persistent memory, tool calling, and tree-of-thought reasoning
- Multi-Agent Collaboration: Built-in LightSwarm for intent recognition and task delegation, simpler multi-agent collaboration than Swarm
- MCP Protocol Support: Connect to MCP servers via stdio and SSE, extending tool and model integration capabilities
- Tree-of-Thought Reasoning: Built-in ToT module with reflection mechanism for complex task decomposition and multi-step reasoning
- LightFlow Workflow Orchestration: Chain agents into deterministic multi-step workflows with DAG dependencies, step output passing, and retries
Use Cases
💡 Rapid AI Agent App Building: Quickly prototype and deploy AI assistants using the lightweight framework
💡 Multi-Agent Collaboration Systems: Build multi-agent teams with autonomous learning capabilities for complex tasks
💡 LLM Tool Integration: Extend agent external interaction capabilities through MCP protocol and custom tools
💡 Production-Grade Agent Deployment: Implement plug-and-play deployment with OpenAI-compatible API output and streaming responses
💡 Long-Term Memory Agents: Build personalized long-term memory per user to improve conversation continuity and intelligence
Categories
Quick Start
1. Install: pip install lightagent
2. Import and initialize agent, configure LLM provider
3. Define tools and skill modules
4. Start agent service, interact via OpenAI-compatible API