AutomateLab-tech/n8n-mcp
by Various
Debugging-first MCP server for n8n. Tools for workflow generation, linting, per-node execution diagnosis, and driving live n8n instances. Built for AI agents.
MCP
AutomateLab-tech/n8n-mcp
Added 7 June 2026
Overview
An open-source MCP server that connects AI agents to n8n. It provides tools for generating workflows, linting them, diagnosing per-node execution, and controlling live n8n instances. Designed for a debugging-first workflow.
Best for
Best for
Developers who want to use AI agents to create and debug n8n workflows programmatically
Use cases
- Generate n8n workflows from natural language prompts
- Debug and fix node execution errors with step-by-step analysis
- Lint existing workflows for compliance with best practices
How to use
Install
npm install -g @automatelab/n8n-mcp Tools exposed
workflow_generatenode_scaffoldworkflow_lintworkflow_diffexecution_explainexecution_replayexecution_timelineworkflow_listworkflow_getworkflow_createworkflow_activateexecution_list
Tested with
Claude Desktop, Cursor
Notes
An open-source MCP server that connects AI agents to n8n. It provides tools for generating workflows, linting them, diagnosing per-node execution, and controlling live n8n instances. Designed for a debugging-first workflow.
7 stars on GitHub. Last updated 2026-05-31. Licensed MIT.
Use cases
- Generate n8n workflows from natural language prompts
- Debug and fix node execution errors with step-by-step analysis
- Lint existing workflows for compliance with best practices
Pros
- Built specifically for agent-driven debugging and workflow creation
- Integrates directly with n8n’s live instances
- Open-source and written in TypeScript
Cons
- Very low adoption (7 stars) indicating limited testing or maturity
- Depends on the Model Context Protocol, which is not standard across all AI agents
- Requires running an MCP server, adding infrastructure overhead
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Built specifically for agent-driven debugging and workflow creation
- Integrates directly with n8n's live instances
- Open-source and written in TypeScript
Cons
- Very low adoption (7 stars) indicating limited testing or maturity
- Depends on the Model Context Protocol, which is not standard across all AI agents
- Requires running an MCP server, adding infrastructure overhead
Open-source & AI alternatives
Swap-in tools that solve the same job. Weigh the trade-offs before you commit.
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