Agent Marketplace

Simple to install, powerful command-line based AI agent system for coding.

Personal-Model First Self Evolving AI Agent 🐘

A decentralized agent network for building collaborative, LLM-powered agent-to-agent (A2A) systems.

GraphBit is the world’s first enterprise-grade Agentic AI framework, built on a Rust core with a Python wrapper for unmatched speed, security, and scalability. It enables reliable multi-agent workflows with minimal CPU and memory usage, making it production-ready for real-world enterprise environments.

Second Brain is an agentic framework that acts as an operating system, using local file intelligence, workflow automation, and LLMs to complete tasks and communicate over multiple modalities and messaging platforms.

Offical Implementation for "Recursive Multi-Agent Systems"

TUI for reviewing diffs, files, and documents with inline annotations

RLAnything (ICML 2026) & AutoTool (ICML 2026), DemyAgent: Open-Source RL for LLMs and Agentic Scenarios

Universal AI Agent Frontend. Build your backend we handle the rest.

AI agents that guide you from idea to working code, with you in control at every step.

👩🏻‍🍳 A collection of example notebooks using Haystack

Self-evolving second brain with 17 AI skills, 6 worker agents, and people CRM — inspired by Garry Tan's gstack and gbrain. Works with Claude Code, Cursor, Kiro, Gemini CLI, Codex.

Open workflow intelligence for discovering, validating, repairing, and generating automation workflows across frameworks — starting with n8n.

ScienceClaw is a personal research assistant built with LangChain DeepAgents and AIO Sandbox infrastructure, adopting a completely new architecture beyond OpenClaw. It offers stronger security, better transparency, and a more user-friendly experience.

🔥🔥🔥 ICLR 2025 Oral. Automating Agentic Workflow Generation.

A distributed framework for LLM agents

The Coordination Layer for Multi-Agent AI

🚀 Universal SDK for building next-gen MCP servers

Agent memory for LLMs: 30 runnable Jupyter notebooks covering conversation buffers, vector stores, knowledge graphs, episodic and semantic memory, MemGPT, Mem0, Letta, Zep, Graphiti, LoCoMo benchmarks, and production patterns.

RAI is a vendor agnostic agentic framework for Physical AI robotics, utilizing ROS 2 tools to perform complex actions, defined scenarios, free interface execution, log summaries, voice interaction and more.

A playground for neuro-san

A Framework for LLM-based Multi-Agent Reinforced Training and Inference

Meta Agents Research Environments is a comprehensive platform designed to evaluate AI agents in dynamic, realistic scenarios. Unlike static benchmarks, this platform introduces evolving environments where agents must adapt their strategies as new information becomes available, mirroring real-world challenges.

The most autonomous agent framework. No approval loops. No babysitting. Configure once, forget forever.