n8n-mcp

作者 czlonkowski已验证

A MCP for Claude Desktop / Claude Code / Windsurf / Cursor to build n8n workflows for you

22,752
Stars
3,631
Forks
TypeScript
语言
2026/8/23
添加时间

⚠️ 第三方软件声明

本 Skill 为第三方开源软件,独立托管于 GitHub。SkillTip 仅为信息目录,不控制或维护底层仓库。所显示的安全检查为自动化且范围有限,安装前请自行审查源码。

阅读服务条款

安装

添加到你的 Claude Code skills 目录:

# Add to your Claude Code skills
git clone https://github.com/czlonkowski/n8n-mcp

快速入门

使用 n8n-mcp 等 Skills 的指南。

安全报告

已验证

上次扫描:—

{
  "status": "PASSED",
  "issues": []
}

README.md

n8n-MCP

License: MIT GitHub stars npm version codecov Tests n8n version Docker Deploy on Railway

A Model Context Protocol (MCP) server that provides AI assistants with comprehensive access to n8n node documentation, properties, and operations. Deploy in minutes to give Claude and other AI assistants deep knowledge about n8n's 2,541 workflow automation nodes (832 core + 1,709 community).

Overview

n8n-MCP serves as a bridge between n8n's workflow automation platform and AI models, enabling them to understand and work with n8n nodes effectively. It provides structured access to:

  • 2,541 n8n nodes - 832 core nodes + 1,709 community nodes (1,441 verified)

  • Node properties - 99% coverage with detailed schemas

  • Node operations - 66.5% coverage of available actions

  • Documentation - 86% coverage from official n8n docs (including AI nodes)

  • AI tools - 267 AI-capable tool variants detected with full documentation

  • Real-world examples - 156 ranked configurations extracted from popular templates

  • Template library - 2,352 workflow templates with 99.96% AI metadata coverage

  • Community nodes - Search verified community integrations with source filter

Support This Project

n8n-mcp started as a personal tool but now helps tens of thousands of developers automate their workflows efficiently. Maintaining and developing this project competes with my paid work. Your sponsorship helps me dedicate focused time to new features, respond quickly to issues, keep documentation up-to-date, and ensure compatibility with latest n8n releases. Become a sponsor

Important Safety Warning

NEVER edit your production workflows directly with AI! Always:

  • Make a copy of your workflow before using AI tools

  • Test in development environment first

  • Export backups of important workflows

  • Validate changes before deploying to production

AI results can be unpredictable. Protect your work!

Quick Start

The fastest way to try n8n-MCP - no installation, no configuration:

dashboard.n8n-mcp.com

  • Free tier: 100 tool calls/day

  • Instant access: Start building workflows immediately

  • Always up-to-date: Latest n8n nodes and templates

  • No infrastructure: We handle everything

Just sign up, get your API key, and connect your MCP client.

Want to self-host? See the Self-Hosting Guide for npx, Docker, Railway, and local installation options.

n8n Integration

Want to use n8n-MCP with your n8n instance? Check out our comprehensive n8n Deployment Guide for:

  • Local testing with the MCP Client Tool node

  • Production deployment with Docker Compose

  • Cloud deployment on Hetzner, AWS, and other providers

  • Troubleshooting and security best practices

Cloudflare Access Authentication

If your n8n instance sits behind Cloudflare Access (Zero Trust), provide your service token so n8n-MCP can authenticate:

  • N8N_CF_CLIENT_ID - Cloudflare Access Client ID

  • N8N_CF_CLIENT_SECRET - Cloudflare Access Client Secret

When set, these are sent as CF-Access-Client-Id / CF-Access-Client-Secret headers on n8n API requests, version/health probes, and webhook executions. The token is confined to the N8N_API_URL origin — webhook calls to a different host (e.g. a split WEBHOOK_URL origin) do not receive it, to avoid leaking the token.

Connect your IDE

n8n-MCP works with multiple AI-powered IDEs and tools:

Add Claude Skills (Optional)

Supercharge your n8n workflow building with specialized skills that teach AI how to build production-ready workflows!

n8n-mcp Skills Setup

Learn more: n8n-skills repository

Claude Project Setup

For the best results when using n8n-MCP with Claude Projects, use these enhanced system instructions:

You are an expert in n8n automation software using n8n-MCP tools. Your role is to design, build, and validate n8n workflows with maximum accuracy and efficiency.

## Core Principles

### 1. Silent Execution
CRITICAL: Execute tools without commentary. Only respond AFTER all tools complete.

### 2. Parallel Execution
When operations are independent, execute them in parallel for maximum performance.

### 3. Templates First
ALWAYS check templates before building from scratch (2,352 available).

### 4. Multi-Level Validation
Use validate_node(mode='minimal') → validate_node(mode='full') → validate_workflow pattern.

### 5. Never Trust Defaults
CRITICAL: Default parameter values are the #1 source of runtime failures.
ALWAYS explicitly configure ALL parameters that control node behavior.

## Workflow Process

1. **Start**: Call `tools_documentation()` for best practices

2. **Template Discovery Phase** (FIRST - parallel when searching multiple)
   - `search_templates({searchMode: 'by_metadata', complexity: 'simple'})` - Smart filtering
   - `search_templates({searchMode: 'by_task', task: 'webhook_processing'})` - Curated by task
   - `search_templates({query: 'slack notification'})` - Text search (default searchMode='keyword')
   - `search_templates({searchMode: 'by_nodes', nodeTypes: ['n8n-nodes-base.slack']})` - By node type

   **Filtering strategies**:
   - Beginners: `complexity: "simple"` + `maxSetupMinutes: 30`
   - By role: `targetAudience: "marketers"` | `"developers"` | `"analysts"`
   - By time: `maxSetupMinutes: 15` for quick wins
   - By service: `requiredService: "openai"` for compatibility

3. **Node Discovery** (if no suitable template - parallel execution)
   - Think deeply about requirements. Ask clarifying questions if unclear.
   - `search_nodes({query: 'keyword', includeExamples: true})` - Parallel for multiple nodes
   - `search_nodes({query: 'trigger'})` - Browse triggers
   - `search_nodes({query: 'AI agent langchain'})` - AI-capable nodes

4. **Configuration Phase** (parallel for multiple nodes)
   - `get_node({nodeType, detail: 'standard', includeExamples: true})` - Essential properties (default)
   - `get_node({nodeType, detail: 'minimal'})` - Basic metadata only (~200 tokens)
   - `get_node({nodeType, detail: 'full'})` - Complete information (~3000-8000 tokens)
   - `get_node({nodeType, mode: 'search_properties', propertyQuery: 'auth'})` - Find specific properties
   - `get_node({nodeType, mode: 'docs'})` - Human-readable markdown documentation
   - Show workflow architecture to user for approval before proceeding

5. **Validation Phase** (parallel for multiple nodes)
   - `validate_node({nodeType, config, mode: 'minimal'})` - Quick required fields check
   - `validate_node({nodeType, config, mode: 'full', profile: 'runtime'})` - Full validation with fixes
   - Fix ALL errors before proceeding

6. **Building Phase**
   - If using template: `get_template(templateId, {mode: "full"})`
   - **MANDATORY ATTRIBUTION**: "Based on template by **[author.name]** (@[username]). View at: [url]"
   - Build from validated configurations
   - EXPLICITLY set ALL parameters - never rely on defaults
   - Connect nodes with proper structure
   - Add error handling
   - Use n8n expressions: $json, $node["NodeName"].json
   - Build in artifact (unless deploying to n8n instance)

7. **Workflow Validation** (before deployment)
   - `validate_workflow(workflow)` - Complete validation
   - `validate_workflow_connections(workflow)` - Structure check
   - `validate_workflow_expressions(workflow)` - Expression validation
   - Fix ALL issues before deployment

8. **Deployment** (if n8n API configured)
   - `n8n_create_workflow(workflow)` - Deploy
   - `n8n_validate_workflow({id})` - Post-deployment check
   - `n8n_update_partial_workflow({id, operations: [...]})` - Batch updates
   - `n8n_test_workflow({workflowId})` - Test workflow execution

## Critical Warnings

### Never Trust Defaults
Default values cause runtime failures. Example:
```json
// FAILS at runtime
{resource: "message", operation: "post", text: "Hello"}

// WORKS - all parameters explicit
{resource: "message", operation: "post", select: "channel", channelId: "C123", text: "Hello"}

Example Availability

includeExamples: true returns real configurations from workflow templates.

  • Coverage varies by node popularity
  • When no examples available, use get_node + validate_node({mode: 'minimal'})

Vali

常见问题

What is n8n-mcp?

n8n-mcp is an open-source mcp servers skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by czlonkowski. A MCP for Claude Desktop / Claude Code / Windsurf / Cursor to build n8n workflows for you. It has 22,752 GitHub stars.

Is n8n-mcp safe to use?

n8n-mcp failed SkillsLLM's automated security scan, which flagged one or more high-severity issues. Review the Security Report section carefully before using it.

How do I install n8n-mcp?

Clone the repository with "git clone https://github.com/czlonkowski/n8n-mcp" and add it to your Claude Code skills directory (see the Installation section above).

What programming language is n8n-mcp written in?

n8n-mcp is primarily written in TypeScript. It is open-source under czlonkowski on GitHub, so you can review or fork the full source.

Are there alternatives to n8n-mcp?

Yes. SkillsLLM lists many other MCP Servers skills you can browse and compare side by side. Open the MCP Servers category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh n8n-mcp against similar tools.

评论 (0)

暂无评论,成为第一个分享想法的人!

n8n

by n8n-io

12

Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.

201,88160,308TypeScript
MCP 服务器apisai-tools
查看详情

Scrapling

by D4Vinci

🕷️ An adaptive Web Scraping framework that handles everything from a single request to a full-scale crawl!

75,9137,581Python
MCP 服务器
查看详情

TrendRadar

by sansan0

⭐AI-driven public opinion & trend monitor with multi-platform aggregation, RSS, and smart alerts.🎯 告别信息过载,你的 AI 舆情监控助手与热点筛选工具!聚合多平台热点 + RSS 订阅,支持关键词精准筛选。AI 智能筛选新闻 + AI 翻译 + AI 分析简报直推手机,也支持接入 MCP 架构,赋能 AI 自然语言对话分析、情感洞察与趋势预测等。支持 Docker ,数据本地/云端自持。集成微信/飞书/钉钉/Telegram/邮件/ntfy/bark/slack 等渠道智能推送。

61,65224,883Python
MCP 服务器
查看详情

context7

by upstash

Context7 Platform -- Up-to-date code documentation for LLMs and AI code editors

61,0602,938TypeScript
MCP 服务器
查看详情

High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph — average repo in milliseconds. 158 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies.

39,9393,219C
MCP 服务器
查看详情

开发者还喜欢

基于喜欢此 Skill 的开发者投票和收藏

ECC

by affaan-m

10

The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.

242,21936,702JavaScript
AI 智能体ai-agentsanthropicclaude-code
查看详情
15

An agentic skills framework & software development methodology that works.

234,96620,863Shell
AI 智能体ai-agentsbrainstorming
查看详情

hermes-agent

by NousResearch

10

The agent that grows with you

234,43747,175Python
AI 智能体ai-agentsagent-orchestration
查看详情

n8n

by n8n-io

12

Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.

201,88160,308TypeScript
MCP 服务器apisai-tools
查看详情

The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.

185,94028,768JavaScript
AI 智能体ai-agentsanthropicclaude-code
查看详情

cc-switch

by farion1231

3

A cross-platform desktop All-in-One assistant for Claude Code, Codex, OpenCode, OpenClaw, Grok Build & Hermes Agent. Only official website: ccswitch.io

128,8688,826Rust
AI 智能体claude-codeai-tools
查看详情