⚒️ Build an MCP server which answers questions with retrieval augmented generation
⚡ 4,338 views · ⚒️ Engineering
Description
Build an MCP Server which has access to a semantic database to perform Retrieval Augmented Generation (RAG)
Tutorial
thumbnail.png Click here to watch the full tutorial on YouTube
How it works
This MCP Server has access to a local semantic database (Qdrant) and answers questions being asked to the MCP Client.
AI Agent Template
Click here to navigate to the AI Agent n8n workflow which uses this MCP server
Warning
This flow only runs local and cannot be executed on the n8n cloud platform because of the MCP Client Community Node.
Installation
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Install n8n + Ollama + Qdrant using the Self-hosted AI starter kit
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Make sure to install Llama 3.2 and mxbai-embed-large as embeddings model.
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Activate the n8n flow
activate n8n flow.png
- Run the “RAG Ingestion Pipeline” and upload some PDF documents
How to use it
- Run the MCP Client workflow and ask a question. It will be either answered by using the semantic database or the search engine API.
More detailed instructions
Missed a step? Find more detailed instructions here: https://brightdata.com/blog/ai/news-feed-n8n-openai-bright-data
🔗 Nodes Used
n8n Form Trigger, Default Data Loader, Qdrant Vector Store, Embeddings Ollama, MCP Server Trigger
📥 Import
Download workflow.json and import into n8n:
Workflow menu → Import from File