Create AI-Ready Vector Datasets from Web Content with Claude, Ollama & Qdrant

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Built by scrapeless official scrapeless official
Created on June 05, 2026

Description

AI-Powered Web Data Pipeline with n8n

How It Works

This n8n workflow builds an AI-powered web data pipeline that automates the entire process of:

Extraction**
Structuring**
Vectorization**
Storage**

It integrates multiple advanced tools to transform messy web pages into clean, searchable vector databases.

Integrated Tools

Scrapeless**
Bypasses JavaScript-heavy websites and anti-bot protections to reliably extract HTML content.

Claude AI**
Uses LLMs to analyze unstructured HTML and generate clean, structured JSON data.

Ollama Embeddings**
Generates local vector embeddings from structured text using the all-minilm model.

Qdrant Vector DB**
Stores semantic vector data for fast and meaningful search capabilities.

Webhook Notifications**
Sends real-time updates when workflows complete or errors occur.

From messy webpages to structured vector data — this pipeline is perfect for building intelligent agents, knowledge bases, or research automation tools.

Setup Steps

1. Install n8n

> Requires Node.js v18 / v20 / v22

npm install -g n8n
n8n
After installation, access the n8n interface via:

URL: http://localhost:5678

2. Set Up Scrapeless

Register at: Scrapeless
Copy your API token
Paste the token into the HTTP Request node labeled "Scrapeless Web Request"

3. Set Up Claude API (Anthropic)

Sign up at Anthropic Console
Generate your Claude API key
Add the API key to the following nodes:
Claude Extractor
AI Data Checker
Claude AI Agent

4. Install and Run Ollama

macOS

brew install ollama

Linux

curl -fsSL https://ollama.com/install.sh | sh
Windows
Download the installer from: https://ollama.com

Start Ollama Server
ollama serve
Pull Embedding Model
ollama pull all-minilm
5. Install Qdrant (via Docker)
docker pull qdrant/qdrant

docker run -d \
--name qdrant-server \
-p 6333:6333 -p 6334:6334 \
-v $(pwd)/qdrant_storage:/qdrant/storage \
qdrant/qdrant
Test if Qdrant is running:
curl http://localhost:6333/healthz

6. Configure the n8n Workflow
Modify the Trigger (Manual or Scheduled)

Input your Target URLs and Collection Name in the designated nodes

Paste all required API Tokens / Keys into their corresponding nodes

Ensure your Qdrant and Ollama services are running

Ideal Use Cases
Custom AI Chatbots

Private Search Engines

Research Tools

Internal Knowledge Bases

Content Monitoring Pipelines

Nodes Used (2)

Code
n8n-nodes-base.code
HTTP Request
n8n-nodes-base.httpRequest