Marketplace de agentes
Una API para acceder a todos los agentes. Descubre e invoca agentes de IA a través de una API unificada — descritos mediante AgentCards abiertas de A2A.
360 agentes
flowcraft
proyectoProduction-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.
azure-openai-llm-notes
proyectoA curated collection of resources for 🌌 Azure OpenAI, 🦙 LLMs (+RAG, Agents). Monthly Updates.
simplepdf-embed
proyectoPDF editor in the browser – add text, checkboxes, pictures, signatures to PDF files. Merge, rotate PDF pages – iframe, script and React component
peerd
proyectoThe first AI agent harness native to the browser. A browser extension that runs a full agent loop where you already work: it drives your tabs, spins up sandboxed compute (JS notebooks, WASM Linux VMs, client-side apps), and shares what it builds peer-to-peer. BYOK, no backend, no telemetry.
azure-openai-llm-wiki
proyectoA curated collection of resources for 🌌 Azure OpenAI, 🦙 LLMs (+RAG, Agents). Monthly Updates.
awesome-azure-openai-llm
proyectoA curated collection of resources for 🌌 Azure OpenAI, 🦙 LLMs (+RAG, Agents). Monthly Updates.
opencow
proyectoOne 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. 🐄
mini-AlphaStar
proyecto(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.
aura
proyectoAURA is a production-tested SRE agent platform you can deploy in minutes. AURA handles the guardrails, APIs, state management, streaming, and failure handling required to put AI to work safely on production infrastructure.
Agents_Failure_Attribution
proyectoBenchmark for automated failure attributions in agentic systems (🏆 ICML 2025 Spotlight)
EDDI
proyectoConfig-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.
llm-leaderboard
proyectoA comprehensive set of LLM benchmark scores and provider prices. (deprecated, read more in README)
Awesome-Agent-Harness
proyectoAgent Harness for Large Language Model Agents: A Survey. Survey on LLM agentharnessengineering with a taxonomy. 110+papers, 23 systems analyzed.
agentica
proyectoOne person, a team of agents. Multi-session CLI that collaborates across terminals; /goal keeps long tasks running; WeChat/WeCom/Feishu gateway lets you call them back when you walk away. Async Python SDK, persistent memory, self-evolving skills.
syftr
proyectosyftr is an agent optimizer that helps you find the best agentic workflows for your budget.
hive
proyectoBrowser-native hive-mind for CLI coding agents — Claude Code, Codex, Gemini, and OpenCode collaborate as real PTY processes via a team protocol.
palico-ai
proyectoBuild, Improve Performance, and Productionize your AI Application
agent-craft
proyectoAI 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
awesome-adk-agents
proyectoCurated collection of AI agents built with Google’s Agent Development Kit (ADK): templates, best practices, and production-ready examples for research, business, automation, education, and more.
SurveyForge
proyecto(ACL-2025 main conference) SurveyForge: On the Outline Heuristics, Memory-Driven Generation, and Multi-dimensional Evaluation for Automated Survey Writing
agentic-ai-engineering
proyectoHands-on tutorials for building AI agents from scratch. Learn LLM APIs, prompt engineering, tool calling, and the agent loop through practical examples.
Awesome-LLM-Reasoning-with-NeSy
proyecto✨✨Latest Advances on Neuro-Symbolic Learning in the era of Large Language Models
Deep-Research-Survey
proyectoA Systematic Survey of Deep Research
agent-systems-handbook
proyectoA practical AI agents handbook covering agent systems, agentic workflows, LangGraph, MCP/A2A, context engineering, agent memory, evaluation, observability, and multi-agent architecture. Current trend focus: Gemini Interactions API and managed agents, emerging agent runtimes, and production AI workflow patterns.