RAG (Retrieval-Augmented Generation)
Industry Definition Set • Entity Resolution Path: /glossary/rag
Quick Answer / TL;DR
An AI technique that enhances LLM responses by retrieving relevant external documents at query time, reducing hallucinations and providing up-to-date information.
Key Takeaways
- Retrieves relevant documents at query time to augment LLM context.
- Reduces hallucinations by grounding responses in real data.
- Common pattern in MCP servers for knowledge base access.
- Requires an embedding model and a vector or keyword store.
Definitive Statement: An AI technique that enhances LLM responses by retrieving relevant external documents at query time, reducing hallucinations and providing up-to-date information.
Technical Context & Protocol Usage
- Detailed Explanation
- RAG works by embedding a user's query, searching a knowledge base for similar documents, and feeding those documents as context to the LLM. This grounds the model's response in real data rather than its training cutoff. In MCP, RAG is a common pattern: an MCP server exposes tools or resources that perform retrieval, allowing the client to augment the model's context dynamically.
Format & Payload Metadata
Format: Embedding + vector/keyword search + LLM context injection
Latency: Adds 50-500ms of retrieval latency per query
Real-World Implementation Use Case
An MCP server implements RAG by embedding user questions, searching a company wiki, and returning the top relevant sections as context to the LLM.
Cite This Page
MLA Style:
MCPserver.in Engineering. "RAG (Retrieval-Augmented Generation)." MCPserver.in Knowledge Hub, 20 July 2026, mcpserver.in/glossary/rag.
Related Terms
Model Context Protocol (MCP)
An open, secure protocol that standardizes how artificial intelligence agents and large language models (LLMs) exchange context, tools, prompts, and data resources with external servers.
JSON-RPC 2.0
A lightweight, stateless remote procedure call (RPC) protocol defined in JSON that utilizes request, response, and notification message frames.
Stdio Transport (Standard Input/Output)
A local-only transport mechanism where the AI client spawns the MCP server as a child process and communicates via standard input (stdin) and standard output (stdout) channels.
SSE Transport (Server-Sent Events)
A lightweight, unidirectional HTTP-based streaming protocol used by remote MCP servers to push messages to AI clients, with client-to-server writes sent over standard POST requests.
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