Building n8n workflows with an AI assistant is faster when the assistant can inspect the actual nodes instead of guessing.
n8n-MCP is an MCP server for AI assistants working with n8n workflows.
It helps you find node documentation, properties, operations, examples, and templates through structured MCP tools—then validate node and workflow configurations before deployment.
Key features:
• Node discovery – searches 2,174 n8n nodes, including core and community nodes
• Configuration detail – exposes node properties and operations through get_node
• Template search – searches a library of 2,352 workflow templates
• Validation tools – checks individual nodes, full workflows, connections, and expressions
• IDE setup guides – includes setup docs for Claude Code, VS Code, Cursor, Windsurf, Codex, and Antigravity
It’s open-source (MIT license).
Link in the reply 👇
Ex google engineer acaba de soltar un curso completo de 1 hora para construir agentes de IA que se mejoran solos, desde cero:
00:00 – Cómo nace un agente que se construye a sí mismo
03:01 – soul.md: el archivo que lo controla todo
30:16 – RAG inteligente: solo traes 20 mensajes relevantes, no los 2.000
31:48 – El loop que sabe cuándo parar solo
35:14 – Detectar el error y arreglar el prompt en el momento
50:22 – Cómo Claude comprime y optimiza tu memoria automáticamente
1 hora de contenido práctico que vale más que la mayoría de cursos de pago sobre agentes.
Míralo completo, guárdalo📚
Alguem criou um jogo de montar data center por 6 dolares e o negocio e viciante.
Voce comeca com o chao vazio, compra racks, monta servidores, passa cada cabo na mao. O detalhe insano: o trafego de cada cliente aparece como bolinhas coloridas passando pelos seus cabos em tempo real.
Quem mexe com infra sabe a dor de cabear rack. Agora imagina fazer isso por diversao.
Voice AI is going to explode in 2026. Here’s what I’m seeing:
1. Dictation has completely changed how I work
I go on walks where I dictate to Otter for 40min. I built an app this weekend while lifting weights. The productivity gain is real.
2. Phone booths everywhere
I visited the offices of two large AI companies last week. They have phone booths everywhere. I watched someone walk into one, dictate, then walk right back out. That’s it.
3. Microphones at every desk
I visited Wispr Flow’s headquarters in October (see pic). Every single employee had a $60 microphone on their desk and can whisper tasks all day long to AI. You cannot hear them even if you’re at the neighboring table.
4. OpenAI says typing is the bottleneck
Alexander Embiricos, head of product for Codex, just went on the @lennysan podcast that the “current underappreciated limiting factor” to AGI-level productivity isn’t model capability, it’s human typing speed.
We are literally being held back by our fingers.