经 AI Skill Hub 精选评估,n8n工作流MCP助手 获评「强烈推荐」。在 GitHub 上收获超过 20.6k 颗 Star,这款MCP工具在功能完整性、社区活跃度和易用性方面表现出色,AI 评分 8.5 分,适合有一定技术背景的用户使用。
为Claude Desktop、Claude Code、Windsurf和Cursor提供的开源MCP工具,专门用于构建和管理n8n工作流。集成AI助手与低代码自动化平台,帮助开发者和业务用户快速创建复杂工作流程。
n8n工作流MCP助手 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
为Claude Desktop、Claude Code、Windsurf和Cursor提供的开源MCP工具,专门用于构建和管理n8n工作流。集成AI助手与低代码自动化平台,帮助开发者和业务用户快速创建复杂工作流程。
n8n工作流MCP助手 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/czlonkowski/n8n-mcp
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"n8n---mcp--": {
"command": "npx",
"args": ["-y", "n8n-mcp"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
# 安装后在 Claude 对话中直接使用 # 示例: 用户: 请帮我用 n8n工作流MCP助手 执行以下任务... Claude: [自动调用 n8n工作流MCP助手 MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入:"列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"n8n___mcp__": {
"command": "npx",
"args": ["-y", "n8n-mcp"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
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 2,691 workflow automation nodes (832 core + 1,859 community).
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:
source filterThese tools require N8N_API_URL and N8N_API_KEY in your configuration.
#### Workflow Management - n8n_create_workflow - Create new workflows with nodes and connections - n8n_get_workflow - Unified workflow retrieval (modes: full, details, structure, minimal) - n8n_update_full_workflow - Update entire workflow (complete replacement) - n8n_update_partial_workflow - Update workflow using diff operations - n8n_delete_workflow - Delete workflows permanently - n8n_list_workflows - List workflows with filtering and pagination - n8n_validate_workflow - Validate workflows in n8n by ID - n8n_autofix_workflow - Automatically fix common workflow errors - n8n_workflow_versions - Version history, diff and rollback over two histories: source: 'local' (the snapshots n8n-mcp takes before it changes a workflow, the default) and source: 'native' (n8n's own workflow history, including UI edits — needs N8N_MCP_ACCESS_TOKEN and the workflow's "Available in MCP" setting) - n8n_deploy_template - Deploy templates from n8n.io directly to your instance with auto-fix
#### Node Resource Discovery - n8n_explore_node_resources - Resolve a node's dynamic dropdown (loadOptions) or resource-locator search (listSearch) values — Slack channels, Google Sheets tabs, model lists — using a real credential, so workflow configs use existing IDs instead of invented ones. Requires N8N_MCP_ACCESS_TOKEN (see Official MCP Setup)
#### Execution Management - n8n_test_workflow - Run a workflow. method: 'auto' (default) triggers it over HTTP through its webhook/form/chat trigger; method: 'prepare'/'pinned'/'direct' run workflows that have no such trigger through n8n's own MCP server (needs N8N_MCP_ACCESS_TOKEN and the workflow's "Available in MCP" setting) - n8n_executions - Unified execution management (list, get, delete) - n8n_evaluations - Run and read evaluation test runs (list runs, aggregated metrics, per-case results on n8n 2.30+; trigger and cancel on 2.32+)
#### Folder Management - n8n_manage_folders - Manage workflow folders (create, list, get, rename, move, delete; n8n 2.19+). Place workflows into folders via n8n_create_workflow's parentFolderId or n8n_update_partial_workflow's moveToFolder operation (n8n 2.32+)
#### Data Table Management - n8n_manage_datatable - Manage n8n data tables, rows and columns (list, get, create, update, delete; addColumn/deleteColumn/renameColumn change an existing table's columns through n8n's own MCP server and need N8N_MCP_ACCESS_TOKEN)
#### Credential Management - n8n_manage_credentials - Manage n8n credentials (list, get, create, update, delete, getSchema)
#### Security & Audit - n8n_audit_instance - Security audit combining n8n's built-in audit API with deep workflow scanning
#### Agents - n8n_manage_agents - Manage n8n Agents (persisted assistants with a model, instructions, tools, skills, tasks, memory and channels) through n8n's instance-level MCP server. Requires N8N_MCP_ACCESS_TOKEN and n8n 2.34+ with the agents module (see Official MCP Setup). This is not the AI Agent workflow node — use get_node for that
#### System Tools - n8n_health_check - Check n8n API connectivity and features, including officialMcp status when N8N_MCP_ACCESS_TOKEN is configured - n8n_list_catalog - List instance-level projects or tags; falls back to n8n's instance-level MCP server for team projects when the Public API doesn't expose them
For the best results when using n8n-MCP with Claude Projects, use these enhanced system instructions:
````markdown 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.
validate_node({nodeType, config, mode: 'minimal'}) - Required fields only (<100ms)
validate_node({nodeType, config, mode: 'full', profile: 'runtime'}) - Full validation with fixes
validate_workflow(workflow) - Connections, expressions, AI tools
n8n_validate_workflow({id}) - Validate deployed workflown8n_autofix_workflow({id}) - Auto-fix common errorsn8n_executions({action: 'list'}) - Monitor execution statusFor governance-sensitive environments, use both env vars together. Fully disable tools that are write/destructive or handle sensitive data (n8n_manage_credentials and n8n_manage_datatable also offer read operations, but are removed entirely here because even reads expose sensitive material):
DISABLED_TOOLS=n8n_create_workflow,n8n_update_full_workflow,n8n_update_partial_workflow,n8n_delete_workflow,n8n_autofix_workflow,n8n_deploy_template,n8n_test_workflow,n8n_manage_credentials,n8n_manage_datatable
For tools that bundle read and write operations under one name, block only the destructive operations while keeping list and get. Use this instead of a full DISABLED_TOOLS entry where the tool's read operations are acceptable — the n8n_manage_datatable and n8n_test_workflow entries below are the alternative to removing those tools entirely as above. The example names every write operation of every tool that has one:
DISABLED_TOOL_OPERATIONS=n8n_executions:delete;n8n_test_workflow:auto,trigger,pinned,direct,expose;n8n_evaluations:run,cancel;n8n_manage_folders:create,rename,move,delete;n8n_workflow_versions:delete,rollback,prune,expose;n8n_manage_agents:create,mutate,call,publish,unpublish,revert,delete,update_integration;n8n_manage_datatable:createTable,updateTable,deleteTable,insertRows,updateRows,upsertRows,deleteRows,addColumn,deleteColumn,renameColumn
Two details are easy to miss when writing your own list. For n8n_test_workflow, all four of auto, trigger, pinned and direct run the workflow (an omitted or blank method counts as auto), leaving only the read-only prepare. And expose is not a value of any operation parameter: it is the exposeToMcp consent write of n8n_test_workflow and n8n_workflow_versions, which enables a workflow's "Available in MCP" setting. Omitting expose leaves that write reachable.
Combine with a read-only n8n API key (Settings → API in your n8n instance) for defence in depth. See Read-Only Deployment Recipe for the full setup guide.
The fastest way to try n8n-MCP - no installation, no configuration:
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.
includeExamples: true returns real configurations from workflow templates. - Coverage varies by node popularity - When no examples available, use get_node + validate_node({mode: 'minimal'})
To use n8n_manage_agents, n8n_explore_node_resources, and the project fallback in n8n_list_catalog, set:
N8N_MCP_ACCESS_TOKEN - MCP API key from n8n Settings → Instance-level MCP → set MCP status to Enabled. This is a separate secret from N8N_API_KEY and should be stored the same way. The MCP endpoint is derived from N8N_API_URL; instances that serve MCP from a split host (N8N_MCP_BASE_URL) are not supported.See Connecting n8n-mcp to n8n's instance-level MCP server for the full setup walkthrough, including how to get the token from the n8n UI, prerequisites, and troubleshooting.
Supercharge your n8n workflow building with specialized skills that teach AI how to build production-ready workflows!
Learn more: n8n-skills repository
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
tools_documentation() for best practices2. 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
创新的MCP实现,将n8n与AI编程助手深度融合。20.6k星体现高热度,TypeScript实现保证质量。弥补AI在复杂工作流设计中的空白。
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。
AI Skill Hub 点评:n8n工作流MCP助手 的核心功能完整,质量优秀。对于Claude Desktop / Claude Code 用户来说,这是一个值得纳入个人工具库的选择。建议先在非生产环境试用,再逐步推广。
| 原始名称 | n8n-mcp |
| 原始描述 | 开源MCP工具:A MCP for Claude Desktop / Claude Code / Windsurf / Cursor to build n8n workflow。⭐20.6k · TypeScript |
| Topics | MCP服务器n8n自动化工作流构建AI集成开源工具 |
| GitHub | https://github.com/czlonkowski/n8n-mcp |
| License | MIT |
| 语言 | TypeScript |
收录时间:2026-05-13 · 更新时间:2026-05-16 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端