n8n + RAG + MCP: Designing an AI Workflow That Knows Where Its Knowledge Comes From

Description and use

<p>The dangerous AI workflow is not the one that says, “I don’t know.”</p> <p>It is the one that gives a confident answer, includes a citation, and still leaves you unable to answer the most important follow-up question:</p> <blockquote> <p>Where did this knowledge actually come from?</p> </blockquote> <p>Was it the current policy document? A stale wiki page? A CRM note? A tool result from an MCP server? A retrieved chunk that looked relevant but belonged to a different product version?</p> <p>This is the problem with many n8n + RAG + MCP architectures. They can move data, call models, retriev

Problem

<p>The dangerous AI workflow is not the one that says, “I don’t know.”</p> <p>It is the one that gives a confident answer, includes a citation, and still leaves you unable to answer the most important follow-up question:</p> <blockquote> <p>Where did this knowledge actually come from?</p> </blockquote> <p>Was it the current policy document? A stale wiki page? A CRM note? A tool result from an MCP server? A retrieved chunk that looked relevant but belonged to a different product version?</p> <p>This is the problem with many n8n + RAG + MCP architectures. They can move data, call models, retriev

Outcome

<p>The dangerous AI workflow is not the one that says, “I don’t know.”</p> <p>It is the one that gives a confident answer, includes a citation, and still leaves you unable to answer the most important follow-up question:</p> <blockquote> <p>Where did this knowledge actually come from?</p> </blockquote> <p>Was it the current policy document? A stale wiki page? A CRM note? A tool result from an MCP server? A retrieved chunk that looked relevant but belonged to a different product version?</p> <p>This is the problem with many n8n + RAG + MCP architectures. They can move data, call models, retriev

Evidence

n8n + RAG + MCP: Designing an AI Workflow That Knows Where Its Knowledge Comes From

Source