Agentes de IA
babyagi
Yohei Nakajima's autonomous task agent - now a self-building agent framework in Python
★ 22,4k estrellasMIT
Ver la guía →arcade-mcp es un proyecto de agentes de IA de código abierto de ArcadeAI (ArcadeAI/arcade-mcp en GitHub). Tiene 1.047 estrellas en GitHub y 119 bifurcaciones, se publica bajo la licencia MIT y se actualizó por última vez en GitHub el 7 de octubre de 2026.
A Python framework for building MCP servers and agent tools.
Know what you want the agent to accomplish before touching any code.
Clone the repo and read the README's requirements section.
Install what's needed and add API keys or configuration.
Run the quickstart example, then iterate from there.
Servers without the boilerplate.
Focus on capabilities, not plumbing.
Secure your tools properly.
Claude, Codex, and other MCP clients.
The lingua franca of agent tooling.
Backed by Arcade's tooling work.
Download the source and move into the project folder.
git clone https://github.com/ArcadeAI/arcade-mcp.git
cd arcade-mcpIsolate dependencies, then install requirements.
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txtLaunch using the entry point shown in the README.
python -m arcade_mcp # check README for the exact commandIt is an open-source project at ArcadeAI/arcade-mcp with 119 forks. Check the contributors tab and recent commits to judge how active maintenance is.
Yes — it's MIT licensed: free to use, modify, and ship commercially. Just keep the license notice in copies.
MCP gives agents a standard way to discover and call tools; arcade-mcp is the scaffolding for building those servers in Python.
Developers whose agents need custom capabilities — internal APIs, proprietary data, special tools.
Clone the repo and follow the README quickstart — the docs at https://docs.arcade.dev walk through setup.
Yohei Nakajima's autonomous task agent - now a self-building agent framework in Python
Langroid: a principled Python framework for building LLM multi-agent applications (from CMU/UW researchers)
A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.
Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat…
Simple workflow patterns for building effective agents on MCP.
The agent that grows with you — a Python framework for adaptive AI agents.
Los demás proyectos de Agentes de IA con más estrellas del catálogo de LibreAI: la lista realista de alternativas si arcade-mcp no es lo que buscas.
A personal AI that really does things — on any OS, with your data staying yours.
An agentic skills framework & software development methodology that works.
Agent harness optimization system with skills, memory and security for Claude Code, Codex and more
The agent that grows with you — a Python framework for adaptive AI agents.
DeepSeek's plugin-based agent harness where everything is a plugin.
Proyectos de Agentes de IA cercanos en el catálogo, los más próximos en estrellas a arcade-mcp: sigue explorando a ambos lados.
Fast, best-practice evaluations for AI model outputs.
Qwen-AgentWorld: a language world model simulating MCP, terminal, web, and OS environments for agents.
Official SDKs for tracing with LangSmith.
An open-source speech language model from Hume.
ByteDance's SandboxFusion: a secure sandbox for running and judging LLM-generated code in 20+ languages.
An open benchmark for browser AI agents on everyday tasks.
Gratis y abierto: consigue el código fuente, dale una estrella al repositorio y empieza a crear.