No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by salacoste · MCP Server · ★ 232
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is mcp-n8n-workflow-builder safe to install? View the security audit →
n8n Workflow Builder MCP Server AI-Powered Workflow Automation Through Natural Language Build, manage, and monitor n8n workflows using Claude AI and Cursor IDE via the Model Context Protocol Features • Quick Start • Documentation • Examples • API Reference 🎯 What is This? n8n Workflow Builder MCP Server transforms workflow automation by enabling you to create and manage n8n workflows through conversational AI. No more manual JSON editing or complex UI navigation—just describe what you
| Stars | 232 |
| Forks | 57 |
| Language | JavaScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 78.5839257545533/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-13 |
| Created | 2025-03-15 |
| Platforms | claude-code, mcp, node |
| Est. Tokens | ~17k |
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mcp-n8n-workflow-builder is 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 . It is categorized as a MCP Server with 232 GitHub stars.
mcp-n8n-workflow-builder is primarily written in JavaScript. It covers topics such as ai-automation, ai-tools, api-management.
You can find installation instructions and usage details in the mcp-n8n-workflow-builder GitHub repository at github.com/salacoste/mcp-n8n-workflow-builder. The project has 232 stars and 57 forks, indicating an active community.
mcp-n8n-workflow-builder is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to mcp-n8n-workflow-builder on Agent Skills Hub include n8n-workflow-builder, flow-like, easy-mcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: