xURL offers a Rust-based CLI that unifies multiple AI agent CLIs under a single agents:// URI scheme, enabling consistent conversation management across providers.
DATAGEN orchestrates eight specialized AI agents using LangGraph to automate data analysis workflows with progressive disclosure and multi-LLM provider support.
egregore uses Claude Code hooks and git-based shared memory to enable persistent, multi-agent collaboration without daemons or network calls. A shell script driven, version-controlled protocol.
AG2 Studio offers a FastAPI + Next.js UI for prototyping multi-agent AI workflows on the AG2 framework. It supports multiple LLMs and skill composition but is a reference, not production-ready.
MCO is a Python CLI tool that orchestrates multiple AI coding agents in parallel, aggregating results with deduplication and consensus, enabling multi-agent review workflows from any AI IDE.
A living catalog of 340+ AI agent tools and frameworks in 2026, with a deep dive into GNAP’s minimal multi-agent coordination approach using git and JSON files.
RsClaw is a Rust-based AI agent engine featuring persistent three-layer memory across sessions, multi-agent delegation, and low resource usage in a single 15MB binary.
CrewAI is a Python framework for autonomous AI agents emphasizing speed, flexibility, and precise control through ‘Crews’ and ‘Flows’. It offers enterprise features for production-grade AI orchestration.
Langflow offers a Python-based visual platform to build and deploy AI agents and workflows with multi-agent orchestration, vector DB support, and enterprise features.
MetaGPT uses a multi-agent system with defined GPT roles following SOPs to automate software development from one-line prompts. It simulates a software company with role-based AI collaboration.
TradingAgents uses specialized LLM agents in a structured bull/bear debate to mimic real trading firms. Supports 10+ LLMs, persistent memory, and CLI/Docker usage.
Cua provides a multi-component open-source stack for building and benchmarking computer-use agents that control full desktops without disrupting user focus, across macOS, Linux, Windows, and Android.
Awesome LLM Apps offers 100+ runnable AI agent and RAG templates for quick LLM app development. It supports multiple providers and advanced multi-agent patterns with minimal setup.
