# RAG vs SKILL vs MCP vs RLM

DevFeed: [RAG vs SKILL vs MCP vs RLM](<https://devfeed.tech/articles/rag-vs-skill-vs-mcp-vs-rlm-29086.md>)

Original publisher: [Read original article](<https://blog.alexewerlof.com/p/rag-vs-skill-vs-mcp-vs-rlm>)

Author: Alex Ewerlöf

Published: 2026-02-25T21:08:33Z

Content type: comparison

Language: en

Sources: [Alex Ewerlof Notes](<https://devfeed.tech/sources/alex-ewerlof-notes.md>)

Topics: [Retrieval Augmented Generation (RAG)](<https://devfeed.tech/topics/retrieval-augmented-generation-rag.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [long-context](<https://devfeed.tech/topics/long-context.md>), [Model Context Protocol](<https://devfeed.tech/topics/model-context-protocol.md>)

Tags: [context-window](<https://devfeed.tech/tags/context-window.md>), [llms](<https://devfeed.tech/tags/llms.md>), [mcp](<https://devfeed.tech/tags/mcp.md>), [rag](<https://devfeed.tech/tags/rag.md>)

## AI overview

This article compares RAG, SKILL, MCP, and RLM as techniques for making generalist LLMs more reliable on specialized tasks. It explains that RAG and RLM extend usable context, while SKILL and MCP provide external tool access, and discusses implementation mechanics, advantages, disadvantages, and when to use each approach.

## Source excerpt

Comparing various techniques to make the models more reliable while working around context window limitation