# Agentic-AI-Tutorial

> Use this tool when you need to build autonomous AI systems that can reason, plan, and interact with their environment. It provides a step-by-step guide to creating agentic AI systems using LangGraph and MCP, from basic LLM calls to complex multi-node agents. With git integration, it streamlines the development process, allowing users to version control and collaborate on their AI projects.

Canonical page: https://skillsregistry.net/skills/zkzkgamal-agentic-ai-tutorial  
JSON: https://api.skillsregistry.net/v1/skills/zkzkgamal-agentic-ai-tutorial

## Description

Step-by-step guide to building agentic AI systems with LangGraph and MCP — from basic LLM calls to multi-node agents that reason, plan, and use real tools.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-01

## Source

- **Source listing:** [GitHub](https://github.com/zkzkGamal/Agentic-AI-Tutorial)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "zkzkgamal-agentic-ai-tutorial"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/zkzkgamal-agentic-ai-tutorial` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/zkzkgamal-agentic-ai-tutorial/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt