RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs

AG-UI: the Agent-User Interaction Protocol. Bring Agents into Frontend Applications.

Memory for 24/7 proactive agents like openclaw (moltbot, clawdbot).

Pocket Flow: 100-line LLM framework. Let Agents build Agents!

An open and fair framework for everyone to build AI agents equipped with powerful skills. Launch your agent, improve the world, your wallet, or both!

The Enterprise-Grade Production-Ready Multi-Agent Orchestration Framework. Website: https://swarms.ai

Democratizing Reinforcement Learning for LLMs

Nexent is a zero-code platform for auto-generating agents — no orchestration, no complex drag-and-drop required. Nexent also offers powerful capabilities for agent running control, data processing and MCP tools.

Optimizing inference proxy for LLMs

An event-driven framework designed to build and orchestrate multi-agent AI systems. It enables seamless integration of AI agents with real-world data sources and systems, facilitating complex, multi-step workflows.

Meet Ava, the WhatsApp Agent

When Philosophy meets AI

🦾 Take control of your AI agents

Lightweight Durable Python Workflows

基于 AI Agent 工作流的修仙世界模拟器，旨在还原智能、开放的仙侠世界。| An open-source Cultivation World Simulator using Agentic Workflow to create a dynamic, emerging Xianxia world.

A security scanner for your LLM agentic workflows

An Open-Source AI Writing Project.

End-to-end Generative Optimization for AI Agents

Atom Agent, automate your workflows by talking to an AI — and let it remember, search, and handle tasks like a real assistant

RAGLight is a modular framework for Retrieval-Augmented Generation (RAG). It makes it easy to plug in different LLMs, embeddings, and vector stores, and now includes seamless MCP integration to connect external tools and data sources.