Post by GenAI Works

MCP, RAG, and Skills are not alternatives. They solve different parts of the same problem. Most people confuse them because they all involve "giving AI more capability." But they operate at completely different layers. MCP: The Connection Layer MCP is about connectivity. Your model can't talk to Slack, search engines, or databases on its own. MCP fixes that with a standardized protocol: → Query comes in → MCP Client picks the right server → Server fetches data or triggers an action → Everything gets sent back to the model Instead of building custom integrations for every tool, MCP gives you one clean interface that works across any agent that speaks the protocol. Use this when your agent needs to work with real-world tools and APIs. RAG: The Knowledge Layer RAG is about grounding. LLMs don't know your private data. RAG fixes that. → Convert your documents into embeddings → Store them in a vector database → Query comes in → retrieve the most relevant chunks → Send those chunks + query + system prompt to the model The answer is now based on your data, not just general training. No hallucinations. No outdated context. Use this when you need accurate answers from your own content — docs, PDFs, internal knowledge bases. Agent Skills: The Execution Layer Skills are about action. This is where your agent stops answering and starts doing. → Run Python code → Read and write files → Call APIs → Automate multi-step tasks The model decides: answer this, or use a skill? Then it executes and returns the result. Use this when your agent needs to take actions, not just respond. How they fit together: This is where most builders get it wrong. You don't choose one. You combine all three. → RAG gives your agent the right knowledge → MCP connects it to tools and systems → Skills let it execute tasks end to end That's why strong agents feel useful. They don't just answer. They fetch, decide, and act. One-line clarity: → MCP = connection layer → RAG = knowledge layer → Skills = execution layer Understand this separation and designing AI systems becomes way easier. Most people understand the difference between AI tools. Very few know how to govern them. If your AI systems make decisions, you need more than tools. You need a framework. In our AI Governance Framework course, you’ll build a complete system: inventory, risk assessment, oversight, and documentation you can use in your company. 15% off with code AIGOV15 until Apr 30 Explore the course: https://lnkd.in/g8ST7XHF #AIcourse #AIcheatsheet #AIcommunity #AI