Marketplace degli agenti

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 — an autonomous AI agent and work engine built solo. It can operate your browser, terminal, files, apps, APIs, skills and tools, remember context, recover from failures, automate workflows, and verify the result. Open source · 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.

Design, conduct and analyze results of AI-powered surveys and experiments. Simulate social science and market research with large numbers of AI agents and LLMs.

This is the repository for the Tool Learning survey.