Learn Low-Code Agentic AI
Low-Code Full-Stack Agentic AI Development using LLMs, n8n, Loveable, UXPilot, Supabase and MCP. Class Videos: https://www.youtube.com/playlist?list=PL0vKVrkG4hWq5T6yqCtUL7ol9rDuEyzBH
What is Learn Low-Code Agentic AI?
Learn Low-Code Agentic AI is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to low-code full-stack agentic ai development using llms, n8n, loveable, uxpilot, supabase and mcp. class videos: https://www.youtube.com/playlist?list=pl0vkvrkg4hwq5t6yqctul7ol9rdueyzbh
Low-Code Full-Stack Agentic AI Development using LLMs, n8n, Loveable, UXPilot, Supabase and MCP. Class Videos: https://www.youtube.com/playlist?list=PL0vKVrkG4hWq5T6yqCtUL7ol9rDuEyzBH
This server falls under the Coding Agents category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- Low-Code Full-Stack Agentic AI Development using LLMs, n8n,
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx learn-low-code-agentic-aiConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Learn Low-Code Agentic AI
The Learn Low-Code Agentic AI repository is an open curriculum for building full-stack agentic AI applications using low-code and no-code tools including n8n for workflow automation, Lovable for frontend generation, Supabase for backend data and vector search, and the Model Context Protocol for connecting AI agents to external tools. It accompanies a video course series and provides hands-on project templates demonstrating patterns like AI helpdesks with retrieval-augmented generation, multi-agent orchestration via n8n, and MCP server integration within n8n workflows. Developers new to AI engineering use it to build production-ready agentic systems without deep LLM infrastructure experience.
Prerequisites
- Node.js 18+ or Python 3.10+ depending on which project templates you follow
- An n8n instance (self-hosted via Docker or n8n.cloud account) for workflow automation
- A Supabase project for backend storage and vector search capabilities
- API keys for at least one LLM provider (OpenAI, Anthropic, or Google Gemini)
- An MCP-compatible client such as Claude Desktop or Claude Code
Clone the curriculum repository
Download the repository to access all project templates, n8n workflow exports, and MCP configuration examples.
git clone https://github.com/panaversity/learn-low-code-agentic-ai.git
cd learn-low-code-agentic-aiSet up n8n
Run n8n locally using Docker. This provides the visual workflow editor and the built-in MCP Client Tool node used throughout the curriculum.
docker run -it --rm --name n8n -p 5678:5678 -v ~/.n8n:/home/node/.n8n docker.n8n.io/n8nio/n8nCreate a Supabase project
Sign up at supabase.com and create a new project. Note the project URL and anon/service role keys — these are needed for database and vector store nodes in n8n.
Import a starter workflow into n8n
In the n8n editor, click Import Workflow and load one of the .json workflow files from the repository. Each workflow demonstrates a different agentic AI pattern.
Configure the MCP Client Tool node in n8n
In your imported n8n workflow, open the MCP Client Tool node and point it at an external MCP server (such as an Airtable or filesystem MCP server) to give the AI agent access to real data.
Connect Claude Desktop to the curriculum's MCP server
If the repository includes a standalone MCP server, add it to your Claude Desktop configuration so you can interact with the curriculum's tooling directly from Claude.
Learn Low-Code Agentic AI Examples
Client configuration
Claude Desktop configuration to run the curriculum's MCP server via npx.
{
"mcpServers": {
"learn-low-code-agentic-ai": {
"command": "npx",
"args": ["learn-low-code-agentic-ai"]
}
}
}Prompts to try
Example prompts for exploring agentic AI patterns covered in the curriculum.
- "Show me how to build an AI helpdesk using n8n with Supabase vector search"
- "What n8n nodes do I need to connect an MCP server to my AI agent workflow?"
- "Generate a Supabase schema for storing user queries and AI responses"
- "Walk me through setting up a multi-agent workflow in n8n where one agent plans and another executes"Troubleshooting Learn Low-Code Agentic AI
n8n Docker container starts but the MCP Client Tool node is not available
The MCP Client Tool node was introduced in n8n version 1.50+. Update your n8n image with `docker pull docker.n8n.io/n8nio/n8n` and restart the container. Check the n8n changelog to confirm the minimum version required.
Supabase vector search returns no results even after inserting embeddings
Ensure you have enabled the pgvector extension in your Supabase project under Database > Extensions. Also verify that the embedding dimension in the n8n Embeddings node matches the dimension of the vector column you created in your table.
LLM API calls fail with authentication errors inside n8n
In n8n, API credentials are stored as Credentials, not environment variables. Create a new credential of the appropriate type (OpenAI API, Anthropic, etc.) in the Credentials panel and reference it in the LLM node, rather than pasting the key directly into node parameters.
Frequently Asked Questions about Learn Low-Code Agentic AI
What is Learn Low-Code Agentic AI?
Learn Low-Code Agentic AI is a Model Context Protocol (MCP) server that low-code full-stack agentic ai development using llms, n8n, loveable, uxpilot, supabase and mcp. class videos: https://www.youtube.com/playlist?list=pl0vkvrkg4hwq5t6yqctul7ol9rdueyzbh It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Learn Low-Code Agentic AI?
Follow the installation instructions on the Learn Low-Code Agentic AI GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Learn Low-Code Agentic AI?
Learn Low-Code Agentic AI works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Learn Low-Code Agentic AI free to use?
Yes, Learn Low-Code Agentic AI is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
Learn Low-Code Agentic AI Alternatives — Similar Coding Agents Servers
Looking for alternatives to Learn Low-Code Agentic AI? Here are other popular coding agents servers you can use with Claude, Cursor, and VS Code.
Dify
★ 142.2kProduction-ready platform for agentic workflow development.
Ruflo
★ 54.0k🌊 The leading agent orchestration platform for Claude. Deploy intelligent multi-agent swarms, coordinate autonomous workflows, and build conversational AI systems. Features enterprise-grade architecture, self-learning swarm intelligence, RAG integrat
Goose
★ 45.7kan open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM
Antigravity Awesome Skills
★ 38.3kInstallable GitHub library of 1,400+ agentic skills for Claude Code, Cursor, Codex CLI, Gemini CLI, Antigravity, and more. Includes installer CLI, bundles, workflows, and official/community skill collections.
AgentScope
★ 25.5kBuild and run agents you can see, understand and trust.
Serena
★ 24.5kA coding agent toolkit that provides IDE-like semantic code retrieval and editing tools, enabling LLMs to efficiently navigate and modify codebases using symbol-level operations instead of basic file reading and string replacements.
Browse More Coding Agents MCP Servers
Explore all coding agents servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.
Set Up Learn Low-Code Agentic AI in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
Ready to use Learn Low-Code Agentic AI?
Browse our complete directory of 33,000+ MCP servers, read setup guides for your editor, and start building with the Model Context Protocol.