YAML File Format

Intro

• YAML is a data serialization language (standard format to transfer the data) just like- XML, JSON.

• YAML stand’s for YAML Ain’t Markup Language.

• File Extension: .yaml OR .yml

NOTE: YAML is superset of JSON: any valid JSON file is also a valid YAML file.

• YAML is too specific on “line separation and indentation“.

• Use cases of YAML file- It can be used to write Docker, Ansible and Kubernetes files.

Basic Syntax of YAML File

Key-Value Pairs

• In this example, we are just assigning the values.

Note: We can put our data in ““ ‘‘ or directly, it will treat it as a value. But we need to add any special character then we need to put it into ““ or ‘‘.

Comments

• Using # we can add the comments to it.

Object

• We can put our whole data into a object like-

• Take care of indentation.

Lists

• Suppose, we are having multiple microservices then we can mention it by using “-“.

• For example-

• More example for a list when having multiple versions-

OR

Boolean

• In YAML file we are having 3 options-

  • True or False

  • On or Off

  • Yes or No

Multi-Line String

• Instead of writing multiline string as-

• Using the “|“ symbol -

• Now, to interpret whole multiline as a single line use “>“ symbol-

Environment Variable

• Use the “$“ sign for this-

Placeholders

• Use “{{ }}“ for this-

Multiple YAML Components in a single file

• We can do this using “---“

Use Case of YAML File in K8S

Now, going above snap, you can easily check and understand the hierarchy of this YAML file.

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MCP Server

Introduction

• MCP is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect your devices to various peripherals and accessories, MCP provides a standardized way to connect AI models to different data sources and tools.

Why MCP ?

• MCP helps you build agents and complex workflows on top of LLMs. LLMs frequently need to integrate with data and tools, and MCP provides:

  • A growing list of pre-built integrations that your LLM can directly plug into

  • The flexibility to switch between LLM providers and vendors

  • Best practices for securing your data within your infrastructure

General architecture

• At its core, MCP follows a client-server architecture where a host application can connect to multiple servers:

• MCP Hosts: Programs like Claude Desktop, IDEs, or AI tools that want to access data through MCP

• MCP Clients: Protocol clients that maintain 1:1 connections with servers

• MCP Servers: Lightweight programs that each expose specific capabilities through the standardized Model Context Protocol

• Local Data Sources: Your computer’s files, databases, and services that MCP servers can securely access

• Remote Services: External systems available over the internet (e.g., through APIs) that MCP servers can connect to

How MCP Works – Simplified Flow

• User Sends Input

  • User message arrives via client (e.g., ChatGPT UI)

• Input Passes Through MCP Server

  • MCP identifies the user, context state, permissions, and system prompt

• Model Invocation

  • Appropriate model is queried with the combined context + input

• Response Generation

  • Output is crafted and returned with any updates to memory/context

• Logging & Updates

  • All changes to context or usage are logged for future reference

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GitHub Copilot

Introduction

• GitHub Copilot is an AI coding assistant that helps you write code faster and with less effort, allowing you to focus more energy on problem solving and collaboration.

What Does GitHub Copilot Do?

GitHub Copilot acts like an AI pair programmer:

• It suggests entire lines or blocks of code as you type.

• It understands natural language comments and converts them into code.

• It supports a wide range of programming languages, with a strong focus on JavaScript, Python, TypeScript, Go, Ruby, and more.

Where You Can Use It

• Visual Studio Code (VS Code)

• Visual Studio

• JetBrains IDEs (like IntelliJ, PyCharm)

GitHub Copilot runs as an extension/plugin.

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Sources-

YAML File- https://youtu.be/1uFVr15xDGg?si=Asoorpbo3QPUU4l3

MCP Sever- https://modelcontextprotocol.io/introduction

GitHub Copilot- https://docs.github.com/en/copilot/about-github-copilot/what-is-github-copilot