Turn a YouTube channel into a second brain with Neo4j GraphRAG and GPT-4o-mini

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1. Workflow Overview

AI powered "Second Brain" that can answer questions about any YouTube channel's content using Neo4j Graph Database and RAG. Turn any YouTube channel into a searchable knowledge base. The AI agent u...

Best for

Internal Wiki automation workflows
AI RAG automation workflows
advanced n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.lmchatopenrouter, @n8n/n8n-nodes-langchain.agent, n8n-nodes-base.if, @n8n/n8n-nodes-langchain.chattrigger, @n8n/n8n-nodes-langchain.memorybufferwindow, @n8n/n8n-nodes-langchain.chat, n8n-nodes-base.stickynote, n8n-nodes-base.httprequesttool

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Hugo Le Poole.

Original n8n.io source

1.1 Workflow description

Title: Turn a YouTube channel into a second brain with Neo4j GraphRAG and GPT-4o-mini
Workflow name: Turn a YouTube channel into a second brain with Neo4j GraphRAG and GPT-4o-mini

AI-powered "Second Brain" that can answer questions about any YouTube channel's content using Neo4j Graph Database and RAG.

Turn any YouTube channel into a searchable knowledge base. The AI agent understands relationships between videos, topics, tools, and concepts - enabling powerful queries like "Which videos talk about automation AND mention n8n?" or "What are the most discussed topics?".

Good to know

Neo4j Aura Free Tier is sufficient for most channels (up to 200k nodes)
Apify credits are required for YouTube scraping (~$5 for 500 videos)
LLM costs are minimal (~$0.01 per video for entity extraction)

How it works

Ingestion Flow: Scrapes YouTube videos via Apify, including titles, descriptions, and transcripts.
Entity Extraction: GPT-4o-mini analyzes each video and extracts Topics, Tools, and Concepts mentioned.
Graph Storage: Data is stored in Neo4j with relationships: Video → COVERS → Topic, Video → USES → Tool, Video → EXPLAINS → Concept.
AI Agent: Receives user questions, generates Cypher queries to search the graph, and returns natural language responses with relevant video links.

How to use

Set up a free Neo4j Aura instance and save credentials
Convert your Neo4j username:password to Base64 for authentication
Configure Apify with your target YouTube channel URL
Run the ingestion workflow to populate the database
Chat with the AI agent to query your video knowledge base

Requirements

Neo4j Aura account (free tier available)
Apify account for YouTube scraping
OpenAI API key (GPT-4o-mini) for entity extraction
Anthropic API key (Claude) or OpenAI for the AI agent

Customization

Modify the system prompt to change response style or language
Add more entity types (e.g., People, Companies, Frameworks)
Connect multiple YouTube channels into one knowledge base
Extend to other content sources (blogs, podcasts, Notion docs)

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - 4.1 mini

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenRouter - lmChatOpenRouter
Config choices: Version 1

Block 2 - Catégorie définition Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 3

Block 3 - 4o mini

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenRouter - lmChatOpenRouter
Config choices: Version 1

Block 4 - sonnet 3.5

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenRouter - lmChatOpenRouter
Config choices: Version 1

Block 5 - If

Type / Role: n8n-nodes-base.if - if
Config choices: Version 2.3

Block 6 - AI Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 3

Block 7 - When chat message received

Type / Role: @n8n/n8n-nodes-langchain.chatTrigger - chatTrigger
Config choices: Version 1.4

Block 8 - 4o

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenRouter - lmChatOpenRouter
Config choices: Version 1

Block 9 - sonnet 4.5

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenRouter - lmChatOpenRouter
Config choices: Version 1

Block 10 - Simple Memory

Type / Role: @n8n/n8n-nodes-langchain.memoryBufferWindow - memoryBufferWindow
Config choices: Version 1.3

Block 11 - Respond to Chat

Type / Role: @n8n/n8n-nodes-langchain.chat - chat
Config choices: Version 1

Block 12 - Sticky Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 13 - Sticky Note1

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 14 - neo4j_query

Type / Role: n8n-nodes-base.httpRequestTool - httpRequestTool
Config choices: Version 4.3

Block 15 - Parseur

Type / Role: @n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices: Version 1.3

Block 16 - Sticky Note2

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 17 - Sticky Note3

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 18 - Vers Neo4j

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.3

Block 19 - Sticky Note4

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 20 - Sticky Note5

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 21 - Sticky Note6

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 22 - Sticky Note7

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 23 - Sticky Note8

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 24 - Wich creator ? How many videos ?

Type / Role: n8n-nodes-base.formTrigger - formTrigger
Config choices: Version 2.3

Showing the first 24 of 28 workflow blocks. Download the JSON for the full node graph.

3. Summary Table

Workflow	Turn a YouTube channel into a second brain with Neo4j GraphRAG and GPT-4o-mini
Complexity	advanced
Nodes	28
Categories	Internal Wiki, AI RAG
Author	Hugo Le Poole
Published	19 Jan 2026

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/12812/12812.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Internal Wiki workflows AI RAG workflows

Frequently asked questions

What does Turn a YouTube channel into a second brain with Neo4j GraphRAG and GPT-4o-mini do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Internal Wiki, AI RAG use case.

Hugo Le Poole

3 workflows

Nodes

@n8n/n8n-nodes-langchain.lmchatopenrouter @n8n/n8n-nodes-langchain.agent n8n-nodes-base.if @n8n/n8n-nodes-langchain.chattrigger @n8n/n8n-nodes-langchain.memorybufferwindow @n8n/n8n-nodes-langchain.chat n8n-nodes-base.stickynote n8n-nodes-base.httprequesttool

Complexity

advanced

Published 19 Jan 2026

Likes 0

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Install path: /data/workflows/12812/12812.json

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Turn a YouTube channel into a second brain with Neo4j GraphRAG and GPT-4o-mini

Workflow preview

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

AI-powered "Second Brain" that can answer questions about any YouTube channel's content using Neo4j Graph Database and RAG.

How it works

How to use

Requirements

Customization

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - 4.1 mini

Block 2 - Catégorie définition Agent

Block 3 - 4o mini

Block 4 - sonnet 3.5

Block 5 - If

Block 6 - AI Agent

Block 7 - When chat message received

Block 8 - 4o

Block 9 - sonnet 4.5

Block 10 - Simple Memory

Block 11 - Respond to Chat

Block 12 - Sticky Note

Block 13 - Sticky Note1

Block 14 - neo4j_query

Block 15 - Parseur

Block 16 - Sticky Note2

Block 17 - Sticky Note3

Block 18 - Vers Neo4j

Block 19 - Sticky Note4

Block 20 - Sticky Note5

Block 21 - Sticky Note6

Block 22 - Sticky Note7

Block 23 - Sticky Note8

Block 24 - Wich creator ? How many videos ?

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions