nanobot
Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat apps
MCP server by makafeli · ★ 547 · updated 6 months ago
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.
Choose your AI client and copy the config.
Add to claude_desktop_config.json — macOS: ~/Library/Application Support/Claude/, Windows: %APPDATA%\Claude\. Then restart Claude.
{
"mcpServers": {
"n8n-workflow-builder": {
"command": "npx",
"args": [
"@makafeli/n8n-workflow-builder"
]
}
}
}Or add to ~/.cursor/mcp.json (global) or .cursor/mcp.json (project).
{
"mcpServers": {
"n8n-workflow-builder": {
"command": "npx",
"args": [
"@makafeli/n8n-workflow-builder"
]
}
}
}Or add to .vscode/mcp.json in your workspace.
{
"servers": {
"n8n-workflow-builder": {
"type": "stdio",
"command": "npx",
"args": [
"@makafeli/n8n-workflow-builder"
]
}
}
}Run in your terminal:
claude mcp add n8n-workflow-builder -- npx @makafeli/n8n-workflow-builderRun the server directly:
npx @makafeli/n8n-workflow-builder"env") in the config.Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat apps
AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents
A MCP for Claude Desktop / Claude Code / Windsurf / Cursor to build n8n workflows for you
The power of Claude Code / GeminiCLI / CodexCLI + [Gemini / OpenAI / OpenRouter / Azure / Grok / Ollama / Custom Model / All Of The Above] working as one.
Open-source agentic workspace enterprises can make their own. Connect the systems you already run — 100+ integrations, MCP, chat tools, apps, browser, local files — with shared memory. Any agent (Claude Code, Codex), any model, or BYOK. Set up in clicks, not months. Local-first: your data never leaves your machines.
Build effective agents using Model Context Protocol and simple workflow patterns