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Large language models (LLMs) are fundamentally changing the world of artificial intelligence and becoming more powerful every day. Leading LLMs such as OpenAI's GPT series, Anthropic's Claude, Google's Gemini, and Meta's Llama models stand out with their different strengths. In this comprehensive guide, we examine in detail the best AI models of 2026, their features, and which use cases they should be preferred for.

MCP (Model Context Protocol) is an open protocol developed by Anthropic that enables artificial intelligence models to communicate with external systems in a standardized way. Playing a role in the AI world similar to what USB-C plays in hardware, MCP offers the modern way to integrate LLMs with databases, APIs, file systems, and third-party services. Announced in late 2024, MCP has quickly become a widely accepted standard in the AI industry.

RAG (Retrieval Augmented Generation) is an innovative AI technique that enables large language models to be enriched with up-to-date and domain-specific information. This approach reduces hallucination in LLMs, provides access to current information, and facilitates integration with enterprise data. RAG systems are used across a wide range of applications, from chatbots to search engines, from customer support to enterprise knowledge management.