Mcp From Scratch

MCP From Scratch 🚀

Mastering Model Context Protocol step by step

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📘 About This Repository

This repository is a complete, structured learning path to master MCP (Model Context Protocol) from beginner to advanced level.

MCP is an open protocol that enables AI models to securely interact with external tools, data sources, and systems using a standardized interface.

This repository is designed for:

• DevOps Engineers
• Platform Engineers
• Cloud Engineersbhuvan-raj/KenanGain
• AI Engineers
• Anyone who wants to build real-world AI tooling systems

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🎯 Objectives

By completing this repository, you will be able to:

• Understand MCP architecture deeply
• Build MCP servers from scratch
• Design secure and scalable MCP tools
• Integrate MCP with DevOps and cloud workflows
• Build AI-powered assistants using MCP

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🧠 What You Will Learn

• MCP fundamentals and architecture
• Tools, resources, prompts, and transports
• JSON schema design for AI tools
• STDIO and HTTP-based MCP servers
• Security and permission boundaries
• DevOps-focused MCP use cases
• Kubernetes, Docker, Terraform, and AWS integrations
• Enterprise-grade MCP system design

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🧭 Learning Path

Level 1 -Foundations

• [Module 1 – Introduction to MCPs](./Introduction%20to%20MCPs/)

Covers the fundamentals of Model Context Protocol, including what MCP is, why it was created, problems with traditional AI integrations, comparisons with plugins and APIs, real-world use cases, and MCP’s role in modern AI systems.

• [Module 2 – MCP Architecture](./MCP%20Architecture/)

Explains the client–server model of MCP, the role of the LLM as the client, responsibilities of the MCP server, communication flow, stateless vs stateful interactions, and key security boundaries for safe and scalable AI integrations.

• [Module 3 – Core MCP Concepts](./Core%20MCP%20Concepts/)

Covers the essential building blocks of MCP, including tools, resources, prompts, transports, JSON schema fundamentals, and input/output validation, providing a foundation for safe and structured AI–tool interactions.

• [Module 4 – MCP Transports](./MCP%20Transports/)

Explains the communication channels between MCP clients and servers, including STDIO and HTTP/S transports, local vs remote MCP servers, when to use each transport, and the tool discovery mechanism for dynamic tool invocation.

• [Module 5 – MCP Data Models](./MCP%20Data%20Models/)

Explains how MCP defines and enforces data contracts, including tool definition structures, input and output schemas, structured error models, response formats, and schema-driven techniques to prevent hallucinations and ensure reliable AI–tool interactions.

Level 2 -MCP Development Basics

• [Module 6 – MCP Development Environment](./MCP%20Development%20Environment/)

Covers the prerequisites and setup for MCP development, including required tools, choosing between Node.js and Python, an overview of the MCP SDK, recommended project folder structure, and running MCP servers locally for hands-on experimentation.

• [Module 7 – Building Your First MCP Server](./Building%20your%20first%20MCP%20Server/)

Walks through creating a basic MCP server from scratch, registering tools, implementing tool logic, returning structured outputs, and applying logging and debugging techniques to build a functional and debuggable MCP server.

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: bhuvan-raj
• Source: bhuvan-raj/mcp-from-scratch
• License: MIT

Install and usage instructions live in the source repository linked above.