Agent Marketplace

LLM-supervised persistent memory for AI agents — graph-based recall, cross-session knowledge, single binary. Works with Claude Code, OpenClaw, and any CLI agent.

AI Agent 教学仓库 | 系统化 LangChain、RAG、LangGraph、MCP 全栈实战代码 | 万字博客详解 | 开源可运行示例 | 从零构建智能体

Browser-native hive-mind for CLI coding agents — Claude Code, Codex, Gemini, and OpenCode collaborate as real PTY processes via a team protocol.

Config-driven engine that turns JSON into production-grade AI agents. Multi-agent orchestration, 12+ LLM providers, MCP/A2A protocols, RAG, persistent memory, and enterprise compliance (EU AI Act, GDPR, HIPAA). Built on Quarkus.

Practical system design, tools, and hands-on resources for building Gen-AI agents & agentic AI systems.

[ICLR'25] OpenRCA: Can Large Language Models Locate the Root Cause of Software Failures?

A comprehensive set of LLM benchmark scores and provider prices. (deprecated, read more in README)

Benchmark for automated failure attributions in agentic systems (🏆 ICML 2025 Spotlight)

(JAIR'2022) A mini-scale reproduction code of the AlphaStar program. Note: the original AlphaStar is the AI proposed by DeepMind to play StarCraft II. JAIR = Journal of Artificial Intelligence Research.

First Principles Framework (FPF): Pattern language and core specification for admissible action in problematic engineering, research, and mixed human/AI work.

One task, one agent, delivered. The open-source platform for task-driven autonomous AI agents.OpenCow assigns an autonomous AI agent to every task — features, campaigns, reports, audits — and delivers them in parallel. Full context. Full control. Every department. 🐄

Llama Agents + Workflows are an event-driven, async-first, step-based way to control the execution flow of AI applications like agents.

A curated collection of resources for 🌌 Azure OpenAI, 🦙 LLMs (+RAG, Agents). Monthly Updates.

Aiden — Autonomous AI agent that operates your computer with prompts: browser control, terminal execution, workflows, tools, recovery systems, and persistent memory. Built solo. AGPL-3.0.

Agentic RAG R1 Framework via Reinforcement Learning

Production-grade Go SDK for building AI agents with long-term memory, knowledge retrieval, and voice — runnable as a library, a daemon, or a real-time pipeline.

Let's reproduce paper simulations of multi-robot systems, formation control, distributed optimization and cooperative manipulation.

🦀️ CRAB: Cross-environment Agent Benchmark for Multimodal Language Model Agents. https://crab.camel-ai.org/

MCPMark is a comprehensive, stress-testing MCP benchmark designed to evaluate model and agent capabilities in real-world MCP use.

Any research. One Claw. 🦞 From any materials to research with fully autonomous & skill-driven researcher.

[EMNLP 2025] Awesome RAG Reasoning Resources

🌍 AppWorld: A Controllable World of Apps and People for Benchmarking Function Calling and Interactive Coding Agent, ACL'24 Best Resource Paper.

Hands-on workshop: Build a multi-agent AI system from scratch — Deep Research Agent + Writing Workflow served as MCP servers. Includes code, slides, and video

An Automated AI Agent Tool for Plotting Your Data in Any Paper's Figure Style.