#LLM Architecture
5 articles found with this tag
MCP vs RAG vs Function Calling – Understanding the Differences Clearly
As LLM architectures mature, teams often struggle to choose between MCP, RAG, and function calling. This article provides a clear, practical comparison of these approaches, explains what each one actually solves, and shows how they work together in real production systems.
Read moreMCP Clients Explained – How Models Consume Context Safely
MCP servers expose context and capabilities, but MCP clients determine how models consume them safely. This article explains the role of an MCP client, how it brokers access between models and systems, and why client-side design is critical for reliability, security, and correctness.
Read moreBuilding Your First MCP Server – A Practical Python Walkthrough
Understanding MCP concepts is important, but real clarity comes from implementation. This article walks step by step through building a simple MCP server in Python, explaining how resources, tools, and prompts are registered and exposed to models in practice.
Read moreMCP Core Concepts Explained – Resources, Tools, and Prompts
After understanding why MCP exists, the next step is mastering its core building blocks. This article explains MCP resources, tools, and prompts in depth, clarifies their responsibilities, and shows how they work together to create safe, scalable LLM systems.
Read moreIntroduction to MCP – Why Context Is the New Infrastructure
Large Language Models are powerful, but without structured context they quickly become unreliable. This article introduces the Model Context Protocol (MCP), explains why context management is now a core infrastructure concern, and shows how MCP enables scalable, safe, and maintainable AI systems.
Read more