Marketplace de agentes

[NeurIPS 2025] Open-source Multi-agent Poster Generation from Papers

A curated list of awesome skills, tools, integrations, and resources for Hermes Agent by Nous Research

Easiest and laziest way for building multi-agent LLMs applications.

"Paper2Slides: From Paper to Presentation in One Click"

A股多Agent投研框架 — 适配A股数据源(龙虎榜/游资/解禁等)，7位分析师基于A股规则的辩论决策，基于TradingAgents深度改造，适配大A。A-share multi-agent investment research framework — 7 AI analysts, bull/bear debate, risk assessment。

Portable AI agent runtime for the JVM. One @Agent class runs on Spring AI, LangChain4j, Anthropic, or 9 more behind one SPI. Token streaming, tool calls, human approvals, and governance over WebSocket, SSE, gRPC, or WebTransport/HTTP3. Speaks MCP, A2A, and AG-UI.

A Comprehensive Benchmark to Evaluate LLMs as Agents (ICLR'24)

大厂发布的AI落地实践、顶尖实验室的最新论文、工业界的真实踩坑记录

Surface AI blindspots before you ship. Put up to 8 AI models on every research, design or coding task.

An open-source research agent system for your Zotero library.

Mirix is a multi-agent personal assistant designed to track on-screen activities and answer user questions intelligently. By capturing real-time visual data and consolidating it into structured memories, Mirix transforms raw inputs into a rich knowledge base that adapts to your digital experiences.

总结Prompt&LLM论文，开源数据&模型，AIGC应用

🚀 EvoAgentX: Building a Self-Evolving Ecosystem of AI Agents

A personal knowledge base that builds and maintains itself. Drop in sources — Claude (or Codex/Gemini) reads them, extracts knowledge, and maintains a persistent interlinked wiki. Works with Claude Code, Codex, OpenCode, Gemini CLI. No API key needed.

A native macOS app that allows users to chat with a local LLM that can respond with information from files, folders and websites on your Mac without installing any other software. Powered by llama.cpp.

Stealth browser automation for AI agents over MCP and the Chrome DevTools Protocol: navigation, network hooks, DOM extraction, and pixel-accurate UI cloning.

Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active Hybrid GraphRAG, DreamService, and self-healing loops.

🔥 Comprehensive survey on Context Engineering: from prompt engineering to production-grade AI systems. hundreds of papers, frameworks, and implementation guides for LLMs and AI agents.

🚀 EvoAgentX: Building a Self-Evolving Ecosystem of AI Agents

Cross-CLI skill for Obsidian: turn your vault into a living AI-first second brain across Claude Code, Codex, Gemini, OpenCode, Hermes, and Pi. 44 commands - self-rewriting notes, local+hybrid semantic search, key-less web research, /obsidian-architect codebase docs, and scheduled agents that maintain the vault while you sleep.

Universal memory layer for AI Agents. It provides scalable, extensible, and interoperable memory storage and retrieval to streamline AI agent state management for next-generation autonomous systems.

Designer Skills Collection: agentic skills, commands, and plugins for design — from research to systems, UI, interaction, and delivery.

🏆 Top-1 on 5+ benchmarks | Web UI | Supports MiroThinker, Claude, Kimi, OpenAI

Must-read Papers on LLM Agents.