Маркетплейс агентов

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

A swarm of disposable agents for unattributable web interaction

Browser Operator - The AI browser with built in Multi-Agent platform! Open source alternative to ChatGPT Atlas, Perplexity Comet, Dia and Microsoft CoPilot Edge Browser

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

II-Researcher: a new open-source framework designed to aid building search / research agents

The open-source multi-agent chat interface that lets you manage multiple agents in one dynamic conversation and add MCP servers for deep research

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.

A powerful browser assistant for vibe surfing 一个开源的AI浏览器智能助手

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

🥇 The strongest free web search plugin for DeepSeek Harness, and the search bridge for every model without native web access. Free, no signup, no API key. Ask the web or X, get structured JSON evidence. | 🥇 全网最强的 DeepSeek Harness 免费联网搜索插件，免费免注册免 API key。为不能联网的模型补上搜索，问网页或 X，拿回结构化 JSON 证据（搜索、抓取、引用）。

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

An autonomous AI scientist: a multi-agent loop over literature, experiments, self-critique and write-up, with deterministic guards against reward-hacking and hallucination.

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

[EMNLP 2025] Awesome RAG Reasoning Resources

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

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

Agentic RAG R1 Framework via Reinforcement Learning

Agentic RAG R1 Framework via Reinforcement Learning

A highly customizable agentic harness for arXiv-ready ML/AI review papers (and beyond). It drives agentic AI like Codex CLI and Claude Code through a gated LaTeX workflow with verified BibTeX citations.

Caura (formerly MemClaw) — governed shared memory for AI agent fleets. Multi-agent, multi-tenant, MCP-native. Trust tiers, keystone policies, audit trails, knowledge graph, self-improving retrieval. Apache 2.0.

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

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

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