Learn Agentic AI

v1.0.0Coding Agentsstable

Build production-grade agents with OpenAI AgentKit, a no-code platfrom.

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What is Learn Agentic AI?

Learn Agentic AI is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to build production-grade agents with openai agentkit, a no-code platfrom.

Build production-grade agents with OpenAI AgentKit, a no-code platfrom.

This server falls under the Coding Agents category on MCPgee, the world's largest MCP server directory with 33,000+ servers.

Features

  • Build production-grade agents with OpenAI AgentKit, a no-cod

Use Cases

Build agents with OpenAI AgentKit
Learn no-code to code agents
Access production-grade agent patterns
panaversity

Maintainer

LicenseMIT
Languagetypescript
Versionv1.0.0
UpdatedMay 8, 2026
Statushealthy
Maintenanceactive

Works with

ClaudeOpenAIwindowsmacoslinux

Installation

Manual Installation

npx learn-agentic-ai-from-low-code-to-code

Configuration

Configuration Details

Config File

claude_desktop_config.json

Performance

Response Metrics

Response Time< 200ms
ThroughputMedium

Resource Usage

Memory UsageLow
CPU UsageLow

How to Set Up and Use Learn Agentic AI

The Learn Agentic AI repository by Panaversity is a structured educational course that guides learners from no-code agent building through to full code-based AI agent development using OpenAI's AgentKit platform. It covers five core AgentKit components: Agent Builder (visual workflow canvas), Connector Registry (for linking knowledge sources and MCP servers), ChatKit (embedded chat interfaces), Evals (quality measurement), and Guardrails (safety and PII protection). The curriculum is designed for both technical and non-technical professionals who want to build production-grade multi-step AI agents without needing to start from scratch with code.

Prerequisites

  • A laptop with a modern web browser (no local software installation required for no-code modules)
  • Access to OpenAI AgentKit features (requires an OpenAI account with AgentKit enabled)
  • Sample documents such as FAQs, policy docs, or SOPs for building knowledge-based agents
  • An MCP-compatible client such as Claude Desktop if integrating MCP servers via the Connector Registry
  • Node.js 18+ for code-based modules in the curriculum
1

Clone the course repository

Clone the Panaversity learn-agentic-ai repository to access course materials, code examples, and project templates.

git clone https://github.com/panaversity/learn-agentic-ai-from-low-code-to-code.git
cd learn-agentic-ai-from-low-code-to-code
2

Review course structure and prerequisites

Read the README to understand the 6-week curriculum (2 sessions/week) or the 2-day intensive bootcamp format. Identify which modules apply to your skill level.

3

Set up your OpenAI AgentKit account

Log in to your OpenAI account and enable AgentKit access. AgentKit is the primary no-code platform used in the early modules of the course.

4

Install code module dependencies

For the code-based modules, install the required Node.js packages from the project directory.

npm install
5

Build your first capstone agent

Follow the course exercises to build one of the capstone agents — such as a customer support triage bot or a research brief generator — using the Agent Builder visual canvas.

6

Connect MCP servers via the Connector Registry

In AgentKit's Connector Registry, add an MCP server endpoint to give your agent access to external tools and knowledge sources.

Learn Agentic AI Examples

Client configuration

Example Claude Desktop config for an MCP server built from this course's code modules.

{
  "mcpServers": {
    "learn-agentic-ai": {
      "command": "npx",
      "args": ["learn-agentic-ai-from-low-code-to-code"]
    }
  }
}

Prompts to try

Prompts relevant to exploring agent-building concepts from the course.

- "Walk me through building a customer support triage agent using OpenAI AgentKit."
- "How do I connect an MCP server as a knowledge source in the AgentKit Connector Registry?"
- "Show me how to use AgentKit Guardrails to mask PII in user inputs before sending to the LLM."

Troubleshooting Learn Agentic AI

AgentKit features are not available in your OpenAI account

AgentKit access may require a specific OpenAI plan or an invitation. Check your account settings or contact OpenAI support to request access.

npm install fails in code-based modules

Ensure you are using Node.js 18 or higher. Run 'node --version' to check, and use nvm to switch versions if needed.

MCP server connection fails in Connector Registry

Verify the MCP server endpoint URL is reachable from the AgentKit environment. For local servers, you may need to use a tunneling tool such as ngrok to expose the endpoint publicly.

Frequently Asked Questions about Learn Agentic AI

What is Learn Agentic AI?

Learn Agentic AI is a Model Context Protocol (MCP) server that build production-grade agents with openai agentkit, a no-code platfrom. It connects AI assistants to external tools and data sources through a standardized interface.

How do I install Learn Agentic AI?

Follow the installation instructions on the Learn Agentic AI GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.

Which AI clients work with Learn Agentic AI?

Learn 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 Agentic AI free to use?

Yes, Learn Agentic AI is open source and available under the MIT license. You can use it freely in both personal and commercial projects.

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.

Quick Config Preview

{ "mcpServers": { "learn-agentic-ai-from-low-code-to-code": { "command": "npx", "args": ["-y", "learn-agentic-ai-from-low-code-to-code"] } } }

Add this to your claude_desktop_config.json or .cursor/mcp.json

Read the full setup guide →

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