Using MCP with n8n? Pair it with 5,000+ paste-ready workflows.
MCP builds the structure — our templates give you proven starting points for Slack, Gmail, AI, and CRM automations.
Control n8n with AI Assistants
MCP (Model Context Protocol) bridges let you build, edit, and deploy n8n workflows using natural language in Claude Desktop, Cursor, or any MCP-compatible AI assistant.
Better together
MCP builds the flow. Templates give you the starting point.
MCP bridges are great at wiring nodes from natural language — but they still need a credible starting pattern. Our library has 5,000+ paste-ready n8n workflows (Slack, Gmail, OpenAI, webhooks, CRM) you can hand your AI assistant as a reference.
How MCP Bridges Work
Install MCP Server
Install an n8n MCP bridge using npm. It connects your AI assistant to your n8n instance.
Chat with Your AI
Describe workflows in plain English: "Create a Slack notification when GitHub issues are opened"
AI Builds It
The MCP bridge creates the workflow in your n8n instance. Test, refine, and deploy!
Example: Building a Workflow with Claude
• GitHub Node (fetch notifications)
• Slack Node (send message)
Compatible AI Assistants
Claude Desktop
Anthropic's AI assistant
Cursor
AI-powered code editor
Other MCP Clients
Any MCP-compatible tool
Available MCP Bridges
Showing 20 of 20 MCP bridges
Editor's picks
The most battle-tested MCP bridges for n8n — ranked by community adoption (GitHub stars). Start here if you're new to MCP.
n8n-mcp
A MCP for Claude Desktop / Claude Code / Windsurf / Cursor to build n8n workflows for you
n8n-nodes-mcp
n8n custom node for MCP
jar-analyzer
Jar Analyzer - 一个 JAR 包 GUI 分析工具，方法调用关系搜索，方法调用链 DFS 算法分析，模拟 JVM 的污点分析验证 DFS 结果，字符串搜索，Java Web 组件入口分析，CFG 程序分析，JVM 栈帧分析，自定义表达式搜索，紧跟 AI 技术发展，支持 MCP 调用，支持 n8n 工作流
n8n-mcp-server
MCP server that provides tools and resources for interacting with n8n API
n8n-workflow-builder
AI assistant integration for n8n workflow automation through Model Context Protocol (MCP). Connect Claude Desktop, ChatGPT, and other AI assistants to n8n for natural language workflow management.
learn-low-code-agentic-ai
Low-Code Full-Stack Agentic AI Development using LLMs, n8n, Loveable, UXPilot, Supabase and MCP. Class Videos: https://www.youtube.com/playlist?list=PL0vKVrkG4hWq5T6yqCtUL7ol9rDuEyzBH
n8n-claw
OpenClaw-inspired autonomous AI agent built entirely in n8n. Adaptive RAG-powered memory, Skills via MCP templates, Expert Agents with delegated sub-agents, proactive task management, media understanding - self-hosted with one setup script
CAAL
Local voice assistant that learns new abilities via auto-discovered n8n workflows exposed as tools via MCP
google-meta-ads-ga4-mcp
MCP server for Google Ads, Meta Ads & GA4 — works with ChatGPT, Claude, Cursor, n8n, Windsurf & more. 250+ tools for campaign management, analytics & optimization.
project-nova
A multi-agent AI architecture that connects 25+ specialized agents through n8n and MCP servers. Project NOVA routes requests to domain-specific experts, enabling control of applications from knowledge bases to DAWs, home automation to development tools. Includes system prompts, Dockerfiles, and workflows for a complete AI assistant ecosystem.
mcp-n8n-workflow-builder
AI-powered n8n workflow automation through natural language. MCP server enabling Claude AI & Cursor IDE to create, manage, and monitor workflows via Model Context Protocol. Multi-instance support, 17 tools, comprehensive docs. Build workflows conversationally without manual JSON editing.
N8N2MCP
Convert N8N agent / workflow into MCP servers, you can use it in Claude / Cursor / Super Chain
n8n-mcp-server
MCP server implementation for n8n workflow automation
n8n-mcp-cc-buildier
No description available
All Bridges
mcp-n8n-builder
🪄 MCP server for programmatic creation and management of n8n workflows. Enables AI assistants to build, modify, and manage workflows without direct user intervention through a comprehensive set of tools and resources for interacting with n8n's REST API.
agentic-archive
n8n-manager-for-ai-agents
End-to-End-Agentic-Ai-Automation-Lab
This repository contains hands-on projects, code examples, and deployment workflows. Explore multi-agent systems, LangChain, LangGraph, AutoGen, CrewAI, RAG, MCP, automation with n8n, and scalable agent deployment using Docker, AWS, and BentoML.