AutomationFlows › Qdrant Vector Store

n8n workflows for Qdrant Vector Store.

All n8n workflows that use the Qdrant Vector Store integration. Each is integration-tagged, privacy-stripped, and importable into your n8n instance in one click.
AI & RAG
Index Local Documents for RAG Using Ollama Embeddings and Qdrant

This workflow ingests a local document file, splits it into chunks, generates embeddings with Ollama (nomic-embed-text), and stores the vectors in a Qdrant collection for on-prem RAG indexing. Runs ma

Read Write File, Qdrant Vector Store, Ollama Embeddings +2
AI & RAG
Sync and Audit Template Vectors with Ollama Embeddings and Qdrant

This workflow runs daily to pull recent community workflow templates from the n8n public catalog API, extract full workflow JSON, sanitize and scan it for potential exposed secrets, generate embedding

HTTP Request, Item Lists, Qdrant Vector Store +2
AI & RAG
Qdrant Vector Database Embedding Pipeline

Qdrant Vector Database Embedding Pipeline. Uses vectorStoreQdrant, manualTrigger, embeddingsOpenAi, documentDefaultDataLoader. Event-driven trigger; 13 nodes.

Qdrant Vector Store, OpenAI Embeddings, Document Default Data Loader +2
AI & RAG
Loading JSON via FTP to Qdrant Vector Database Embedding Pipeline

🧠 This workflow is designed for one purpose only, to bulk-upload structured JSON articles from an FTP server into a Qdrant vector database for use in LLM-powered semantic search, RAG systems, or AI as

Qdrant Vector Store, OpenAI Embeddings, Document Default Data Loader +2
AI & RAG
RAG Whatsapp

RAG Whatsapp. Uses @devlikeapro/n8n-nodes-waha, agent, lmChatOpenAi, embeddingsOpenAi. Event-driven trigger; 13 nodes.

@Devlikeapro/N8N Nodes Waha, Agent, OpenAI Chat +4
AI & RAG
Appflowy Content Sync to Vector Store

AppFlowy Content Sync to Vector Store. Uses n8n-nodes-appflowy, textSplitterRecursiveCharacterTextSplitter, documentDefaultDataLoader, embeddingsOllama. Event-driven trigger; 11 nodes.

N8N Nodes Appflowy, Text Splitter Recursive Character Text Splitter, Document Default Data Loader +3
AI & RAG
RAG Search Agent

RAG Search Agent. Uses executeWorkflowTrigger, agent, lmChatOpenAi, toolVectorStore. Event-driven trigger; 11 nodes.

Execute Workflow Trigger, Agent, OpenAI Chat +3
AI & RAG
Agente_ecommerce_v3_subflujo

Agente_Ecommerce_v3_subflujo. Uses embeddingsGoogleGemini, vectorStoreQdrant, executeWorkflowTrigger, textSplitterRecursiveCharacterTextSplitter. Event-driven trigger; 10 nodes.

Google Gemini Embeddings, Qdrant Vector Store, Execute Workflow Trigger +3
AI & RAG
Google Drive PDF → Qdrant RAG Indexer

Google Drive PDF → Qdrant RAG Indexer. Uses googleDrive, vectorStoreQdrant, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter. Event-driven trigger; 10 nodes.

Google Drive, Qdrant Vector Store, Document Default Data Loader +3
AI & RAG
Fluidflow Slack Triage Bot

Fluidflow Slack Triage Bot. Uses slack, slackTrigger, lmChatOpenAi, vectorStoreQdrant. Event-driven trigger; 8 nodes.

Slack, Slack Trigger, OpenAI Chat +4
AI & RAG
Ingest Vector Store Ecommerce

Ingest Vector Store Ecommerce. Uses readWriteFile, vectorStoreQdrant, embeddingsOpenAi, documentDefaultDataLoader. Event-driven trigger; 8 nodes.

Read Write File, Qdrant Vector Store, OpenAI Embeddings +2
AI & RAG
Ingest Vector Store

Ingest Vector Store. Uses readWriteFile, vectorStoreQdrant, embeddingsOpenAi, documentDefaultDataLoader. Event-driven trigger; 8 nodes.

Read Write File, Qdrant Vector Store, OpenAI Embeddings +2
AI & RAG
My Workflow 22

My workflow 22. Uses vectorStoreQdrant, documentDefaultDataLoader, embeddingsGoogleGemini. Webhook trigger; 7 nodes.

Qdrant Vector Store, Document Default Data Loader, Google Gemini Embeddings
AI & RAG
Ingest Documents

ingest_documents. Uses readBinaryFile, textSplitterRecursiveCharacterTextSplitter, embeddingsOpenAi, vectorStoreQdrant. Event-driven trigger; 5 nodes.

Read Binary File, Text Splitter Recursive Character Text Splitter, OpenAI Embeddings +1
AI & RAG
Tool Search Products

tool_search_products. Uses executeWorkflowTrigger, embeddingsOpenAi, vectorStoreQdrant. Event-driven trigger; 4 nodes.

Execute Workflow Trigger, OpenAI Embeddings, Qdrant Vector Store
AI & RAG
RAG Pipeline

RAG Pipeline. Uses formTrigger, vectorStoreQdrant, embeddingsOllama, documentDefaultDataLoader. Event-driven trigger; 13 nodes.

Form Trigger, Qdrant Vector Store, Ollama Embeddings +6
AI & RAG
Local Chatbot with Retrieval Augmented Generation (rag)

Click here to view the YouTube Tutorial

Form Trigger, Qdrant Vector Store, Ollama Embeddings +6
AI & RAG
Simple Vector Db

simple_vector_db. Uses googleDriveTrigger, googleDrive, vectorStoreQdrant, embeddingsOpenAi. Event-driven trigger; 13 nodes.

Google Drive Trigger, Google Drive, Qdrant Vector Store +6
AI & RAG
Jobmatch AI V3 (ultimate Enterprise Architecture)

JobMatch AI V3 (Ultimate Enterprise Architecture). Uses agent, toolVectorStore, vectorStoreQdrant, embeddingsGoogleGemini. Webhook trigger; 13 nodes.

Agent, Tool Vector Store, Qdrant Vector Store +4
AI & RAG
Answer Document Questions with Ollama and Qdrant Retrieval Chat Bot

This workflow provides a local RAG chatbot in n8n that answers chat questions using context retrieved from a Qdrant collection, generating responses with a local Ollama chat model and Ollama embedding

Chat Trigger, Chain Retrieval Qa, Ollama Chat +3
AI & RAG
RAG Agent (vector Store Qdrant)

RAG Agent. Uses vectorStoreQdrant, documentDefaultDataLoader, agent, chatTrigger. Event-driven trigger; 12 nodes.

Qdrant Vector Store, Document Default Data Loader, Agent +5
AI & RAG
Implement On-prem RAG with Qdrant and Ollama for a Self-hosted Kb

Provides one workflow to maintain the knowledge base and another one to query the knowledge base. Uploaded documents are saved into the Qdrant vector store. When a query is made, the most relevant doc

Document Default Data Loader, Ollama Embeddings, Chat Trigger +5
AI & RAG
Build a Document-based AI Chatbot with Google Drive, Llama 3, and Qdrant RAG

Overview This template allows users to set up an AI-powered chatbot that retrieves and processes knowledge from Google Drive documents using Retrieval-Augmented Generation (RAG). By leveraging Llama 3

Google Drive Trigger, Google Drive, Ollama Embeddings +6
AI & RAG
Noc Zabbix AI Triage Agent

noc_zabbix_ai_triage_agent. Uses agent, memoryRedisChat, lmChatOllama, outputParserStructured. Webhook trigger; 11 nodes.

Agent, Memory Redis Chat, Ollama Chat +6
AI & RAG
Chatbot (memory Mongo Db Chat)

Chatbot. Uses memoryMongoDbChat, httpRequestTool, lmChatMistralCloud, agent. Webhook trigger; 9 nodes.

Memory Mongo Db Chat, HTTP Request Tool, Lm Chat Mistral Cloud +3
AI & RAG
Chatbot (agent)

Chatbot. Uses agent, lmChatGoogleGemini, vectorStoreQdrant, embeddingsGoogleGemini. Webhook trigger; 9 nodes.

Agent, Google Gemini Chat, Qdrant Vector Store +2
AI & RAG
Build an Mcp Server Which Answers Questions with Retrieval Augmented Generation

Click here to watch the full tutorial on YouTube

Mcp Trigger, Qdrant Vector Store, Ollama Embeddings +2
AI & RAG
Upload Brochures to Qdrant (manual Trigger)

Upload Brochures to Qdrant (Manual Trigger). Uses googleDrive, vectorStoreQdrant, embeddingsOpenAi, documentDefaultDataLoader. Event-driven trigger; 8 nodes.

Google Drive, Qdrant Vector Store, OpenAI Embeddings +2
AI & RAG
Consulta

Consulta. Uses agent, lmChatOllama, memoryBufferWindow, vectorStoreQdrant. Webhook trigger; 7 nodes.

Agent, Ollama Chat, Memory Buffer Window +2
AI & RAG
Dssat RAG (embeddings Open Ai)

dssat-rag. Uses embeddingsOpenAi, documentDefaultDataLoader, textSplitterCharacterTextSplitter, vectorStoreQdrant. Event-driven trigger; 7 nodes.

OpenAI Embeddings, Document Default Data Loader, Text Splitter Character Text Splitter +2
AI & RAG
Conversational RAG

Conversational RAG. Uses embeddingsOpenAi, chatTrigger, agent, lmChatOpenAi. Chat trigger; 7 nodes.

OpenAI Embeddings, Chat Trigger, Agent +3
AI & RAG
Small Dick

small dick. Uses executeWorkflowTrigger, vectorStoreQdrant, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter. Event-driven trigger; 6 nodes.

Execute Workflow Trigger, Qdrant Vector Store, Document Default Data Loader +2
AI & RAG
Ingesta

Ingesta. Uses vectorStoreQdrant, embeddingsOllama, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter. Event-driven trigger; 6 nodes.

Qdrant Vector Store, Ollama Embeddings, Document Default Data Loader +3
AI & RAG
Carga De Datos

Carga de datos. Uses vectorStoreQdrant, embeddingsOllama, documentDefaultDataLoader, readWriteFile. Scheduled trigger; 6 nodes.

Qdrant Vector Store, Ollama Embeddings, Document Default Data Loader +2
AI & RAG
Dssat RAG Webhook

dssat-rag-webhook. Uses embeddingsOpenAi, agent, lmChatOpenAi, vectorStoreQdrant. Webhook trigger; 6 nodes.

OpenAI Embeddings, Agent, OpenAI Chat +1
AI & RAG
[vorlage] Agent — RAG (qdrant Wissensbasis)

[Vorlage] Agent — RAG (Qdrant Wissensbasis). Uses chatTrigger, agent, lmChatOllama, vectorStoreQdrant. Chat trigger; 6 nodes.

Chat Trigger, Agent, Ollama Chat +2
AI & RAG
Qa-chain

QA-chain. Uses executeWorkflowTrigger, chainRetrievalQa, lmChatOpenAi, retrieverVectorStore. Event-driven trigger; 6 nodes.

Execute Workflow Trigger, Chain Retrieval Qa, OpenAI Chat +3
AI & RAG
Knowledge Ingestion

Knowledge ingestion. Uses documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, vectorStoreQdrant, embeddingsOpenAi. Event-driven trigger; 6 nodes.

Document Default Data Loader, Text Splitter Recursive Character Text Splitter, Qdrant Vector Store +2
AI & RAG
Rag_qdrant

RAG_qdrant. Uses formTrigger, embeddingsOllama, vectorStoreQdrant, documentDefaultDataLoader. Event-driven trigger; 5 nodes.

Form Trigger, Ollama Embeddings, Qdrant Vector Store +2
AI & RAG
Knowledge Base Upload

Knowledge Base Upload. Uses vectorStoreQdrant, documentDefaultDataLoader, textSplitterTokenSplitter, embeddingsOpenAi. Event-driven trigger; 5 nodes.

Qdrant Vector Store, Document Default Data Loader, Text Splitter Token Splitter +2

40 of 240 workflows on page 2 of 2 · Browse all →

FAQ

How many n8n Qdrant Vector Store workflows are in the catalog?

240 n8n workflows in AutomationFlows currently use the Qdrant Vector Store integration — triggers, actions, or both.

How do I connect Qdrant Vector Store in n8n?

After importing the workflow JSON, n8n will prompt for Qdrant Vector Store credentials on the relevant nodes. AutomationFlows strips credential IDs before publishing — you'll add your own.

Can I combine these with other integrations?

Yes — most Qdrant Vector Store workflows pair with adjacent tools (Slack alerts, Google Sheets logging, OpenAI summarisation). Browse the integration tags on each workflow page to discover pairings.