University of Kwazulu-Natal

Free Video Model Context Protocol Mcp Explained How To Give Ai

Bonisiwe Shabane
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free video model context protocol mcp explained how to give ai

Apps can't correct your pronunciation or answer your questions. Preply tutors can. Join millions making real progress with 1-on-1 lessons from $10/hr. Satisfaction guaranteed. 00:00 - Coming up ...00:47 - TL;DR02:00 - Level 0: Bare LLMs05:35 - Level 1: LLMs + Tools08:20 - Level 2: LLMs + Tools + APIs12:02 - Level 3: LLMs + MCP14:54 - Why... Start your review of Model Context Protocol (MCP) Explained with Code Examples

The Model Context Protocol (MCP) is an open standard and open-source framework introduced by Anthropic in November 2024 to standardize the way artificial intelligence (AI) systems like large language models (LLMs) integrate and share... MCP was announced by Anthropic in November 2024 as an open standard[5] for connecting AI assistants to data systems such as content repositories, business management tools, and development environments.[6] It aims to address the... Earlier stop-gap approaches—such as OpenAI's 2023 "function-calling" API and the ChatGPT plug-in framework—solved similar problems but required vendor-specific connectors.[7] MCP re-uses the message-flow ideas of the Language Server Protocol (LSP) and is transported over... In December 2025, Anthropic donated the MCP to the Agentic AI Foundation (AAIF), a directed fund under the Linux Foundation, co-founded by Anthropic, Block and OpenAI, with support from other companies.[9] The protocol was released with software development kits (SDKs) in programming languages including Python, TypeScript, C# and Java.[8][10] Anthropic maintains an open-source repository of reference MCP server implementations for enterprise systems.[citation needed] Posted on Dec 27 • Originally published at pockit.tools

If you've been building AI applications in 2025, you've probably hit the same wall everyone else has: your LLM is brilliant at generating text, but connecting it to real-world data and tools feels like... Enter the Model Context Protocol (MCP)—an open standard that's quietly becoming as fundamental to AI development as REST APIs are to web development. Originally developed by Anthropic and now adopted across the industry, MCP is solving one of the biggest headaches in AI engineering: how do you give your AI agent reliable, structured access to the outside... In this comprehensive guide, we'll explore what MCP is, why it matters, how it works under the hood, and most importantly—how to implement it in your own AI applications. Before diving into MCP, let's understand the pain it addresses. For years, large language models (LLMs) have been evolving at breakneck speed.

From GPT-4 to Claude and open-source models like LLaMA, the intelligence of AI systems has rapidly improved. Yet beneath this progress lies a quiet but critical limitation; models still struggle to interact reliably with external tools, data sources, and real-world systems in a standardized way. This is where the Model Context Protocol (MCP) enters the conversation. MCP is not a new model, framework, or API wrapper. Instead, it represents a standardized protocol for how AI models receive, interpret, and act on contextual information from tools, databases, files, and services. As AI systems increasingly function as agents rather than passive chatbots, MCP is emerging as a foundational layer for safe, scalable, and interoperable AI.

This article explores what MCP is, why it matters, how it works, and its implications for the future of AI systems. The Model Context Protocol (MCP) is a structured communication standard that defines how external tools and systems provide context to AI models and how models understand, reason about, and use that context. In simpler terms, MCP answers a critical question: This blog post is about something that I find incredibly powerful and transformative: the Model Context Protocol (MCP). After exploring various AI integration approaches, I've written this post to make MCP easy to understand for everyone. In this post, I'll explain what MCP is and why it matters, walk through how it works, and show you how to use it in your projects.

I will show you how to create your own MCP server and examples of using existing ones. Imagine you have a powerful AI assistant that can help with coding, data analysis, or customer support. Now imagine that assistant is locked in a room – it's smart but has no direct access to your databases, files, or tools. If you want it to use some information, you have to manually hand it over. Frustrating, right? This is the situation many LLMs have faced: they're isolated from the vast context and tools that could make them truly useful.

It's like having a brilliant consultant who can only work with the documents you physically bring to them, with no way to search for information or use tools on their own.

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