n8n AI Workflows

Deploy n8n on Clore.ai — self-host a powerful AI workflow automation platform with 400+ integrations and native LLM agent support for pennies per hour.

Overview

n8n is a fair-code workflow automation platform with 55K+ GitHub stars. Unlike fully closed-source alternatives (Zapier, Make), n8n lets you self-host the entire stack — with complete data control — while offering native AI agent capabilities, a JavaScript/Python code node, and a growing library of 400+ integrations.

On Clore.ai, n8n itself runs on CPU (no GPU required), but pairs powerfully with GPU-accelerated services like Ollama or vLLM running on the same server, giving you a completely local AI automation stack. You can have a production n8n instance running for under $0.10–0.20/hr.

Key capabilities:

• 🔗 400+ integrations — Slack, GitHub, Google Sheets, Postgres, HTTP Request, webhooks, and much more

• 🤖 AI Agent nodes — built-in LangChain-powered agents with tool use and memory

• 💻 Code nodes — run arbitrary JavaScript or Python inline in workflows

• 🔄 Trigger variety — webhooks, cron schedules, database polling, email, queue events

• 📊 Sub-workflows — modular, reusable workflow components

• 🔐 Credential vault — encrypted storage for API keys and OAuth tokens

• 🏠 Self-hosted — your data never leaves your server

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Requirements

n8n is a Node.js application packaged as a Docker image. It is CPU-only — no GPU needed for the automation engine itself. A GPU becomes useful only if you're running a local LLM alongside it (e.g. Ollama).

Configuration	GPU	VRAM	System RAM	Disk	Clore.ai Price
Minimal (n8n only)	None / CPU	—	2 GB	10 GB	~$0.03/hr (CPU)
Standard	None / CPU	—	4 GB	20 GB	~$0.05/hr
+ Local LLM (Ollama)	RTX 3090	24 GB	16 GB	60 GB	$0.07–0.21/hr
+ High-throughput LLM	A100 40 GB	40 GB	32 GB	100 GB	bare metal
AI Starter Kit (full)	RTX 4090	24 GB	32 GB	100 GB	$0.14–0.42/hr

Tip: The n8n Self-hosted AI Starter Kit bundles n8n + Ollama + Qdrant + PostgreSQL into one Docker Compose stack. See AI Starter Kit below.

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Quick Start

1. Rent a Clore.ai server

Log in to clore.ai and deploy a server:

• CPU-only instance if you only need n8n automation

• RTX 3090/4090 if you want local LLMs via Ollama

• Expose port 5678 in the offer's port mapping settings

• Enable SSH access

2. Connect to the server

ssh root@<clore-server-ip> -p <ssh-port>

# Verify Docker is installed
docker --version
docker compose version

3. Option A — Minimal single-container start

The fastest way to get n8n running:

# Create a named volume for persistence
docker volume create n8n_data

# Run n8n
docker run -d \
  --name n8n \
  --restart unless-stopped \
  -p 5678:5678 \
  -v n8n_data:/home/node/.n8n \
  -e N8N_HOST=<clore-server-ip> \
  -e N8N_PORT=5678 \
  -e N8N_PROTOCOL=http \
  -e WEBHOOK_URL=http://<clore-server-ip>:5678/ \
  docker.n8n.io/n8nio/n8n

# Check logs
docker logs -f n8n

Access the UI at http://<clore-server-ip>:5678

4. Option B — Docker Compose with Postgres (production)

For production use, replace the default SQLite with Postgres:

mkdir n8n-prod && cd n8n-prod
cat > docker-compose.yml << 'EOF'
version: "3.8"

services:
  postgres:
    image: postgres:15-alpine
    restart: unless-stopped
    environment:
      POSTGRES_USER: n8n
      POSTGRES_PASSWORD: n8npassword   # Change this!
      POSTGRES_DB: n8n
    volumes:
      - postgres_data:/var/lib/postgresql/data
    healthcheck:
      test: ["CMD-SHELL", "pg_isready -U n8n"]
      interval: 10s
      timeout: 5s
      retries: 5

  n8n:
    image: docker.n8n.io/n8nio/n8n
    restart: unless-stopped
    depends_on:
      postgres:
        condition: service_healthy
    ports:
      - "5678:5678"
    environment:
      DB_TYPE: postgresdb
      DB_POSTGRESDB_HOST: postgres
      DB_POSTGRESDB_PORT: 5432
      DB_POSTGRESDB_DATABASE: n8n
      DB_POSTGRESDB_USER: n8n
      DB_POSTGRESDB_PASSWORD: n8npassword
      N8N_HOST: <clore-server-ip>
      N8N_PORT: 5678
      N8N_PROTOCOL: http
      WEBHOOK_URL: http://<clore-server-ip>:5678/
      N8N_ENCRYPTION_KEY: your-32-char-encryption-key-here
      EXECUTIONS_MODE: regular
      N8N_BASIC_AUTH_ACTIVE: "true"
      N8N_BASIC_AUTH_USER: admin
      N8N_BASIC_AUTH_PASSWORD: changeme!
    volumes:
      - n8n_data:/home/node/.n8n

volumes:
  postgres_data:
  n8n_data:
EOF

docker compose up -d
docker compose logs -f n8n

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AI Starter Kit (Recommended)

The n8n Self-hosted AI Starter Kit is the fastest path to a full local AI automation stack. It ships:

• n8n — workflow automation

• Ollama — local LLM inference (GPU or CPU)

• Qdrant — vector database for RAG

• PostgreSQL — persistent storage

# Clone the starter kit
git clone https://github.com/n8n-io/self-hosted-ai-starter-kit.git
cd self-hosted-ai-starter-kit

# For GPU-enabled servers (RTX 3090, 4090, A100, etc.)
docker compose --profile gpu-nvidia up -d

# For CPU-only servers
docker compose --profile cpu up -d

# Monitor startup
docker compose logs -f

# Pull a model into Ollama (after stack starts)
docker exec ollama ollama pull llama3:8b
docker exec ollama ollama pull nomic-embed-text  # For embeddings

Services after startup:

Service	URL
n8n UI	http://<ip>:5678
Ollama API	http://<ip>:11434
Qdrant UI	http://<ip>:6333/dashboard

Note: Ollama with GPU requires the NVIDIA Container Toolkit, which Clore.ai servers have pre-installed.

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Configuration

Environment variables reference

# ── Core settings ────────────────────────────────────────────────────────────
N8N_HOST=0.0.0.0                  # Bind address
N8N_PORT=5678                     # Port to listen on
N8N_PROTOCOL=http                 # http or https
WEBHOOK_URL=http://<ip>:5678/     # Public webhook base URL (critical!)

# ── Encryption ───────────────────────────────────────────────────────────────
N8N_ENCRYPTION_KEY=<32-char-key>  # Encrypts stored credentials
# Generate: openssl rand -hex 16

# ── Authentication ───────────────────────────────────────────────────────────
N8N_BASIC_AUTH_ACTIVE=true
N8N_BASIC_AUTH_USER=admin
N8N_BASIC_AUTH_PASSWORD=your-secure-password

# ── Execution settings ───────────────────────────────────────────────────────
EXECUTIONS_MODE=regular           # regular (single) or queue (Redis-backed)
EXECUTIONS_DATA_SAVE_ON_SUCCESS=all
EXECUTIONS_DATA_SAVE_ON_ERROR=all
EXECUTIONS_DATA_MAX_AGE=336       # Keep execution data for 14 days

# ── Timezone ─────────────────────────────────────────────────────────────────
GENERIC_TIMEZONE=UTC

# ── Disable telemetry (optional) ─────────────────────────────────────────────
N8N_DIAGNOSTICS_ENABLED=false
N8N_VERSION_NOTIFICATIONS_ENABLED=false

Connecting n8n to Ollama for AI agents

Once Ollama is running on the same server:

1. In n8n, add a new credential: Ollama API

   • Base URL: http://ollama:11434 (if using Compose) or http://localhost:11434

2. In a workflow, add an AI Agent node

3. Under Chat Model, select Ollama and choose your model (e.g. llama3:8b)

4. Add tools like HTTP Request, Postgres, or Code nodes

5. Execute!

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Tips & Best Practices

Cost optimization on Clore.ai

# Export all workflows before stopping your instance
# Use n8n CLI inside the container:
docker exec n8n n8n export:workflow --all --output=/home/node/.n8n/workflows-backup.json

# Copy backup to local machine
docker cp n8n:/home/node/.n8n/workflows-backup.json ./n8n-workflows-backup.json

# Import on a new instance:
docker exec n8n n8n import:workflow --input=/home/node/.n8n/workflows-backup.json

Webhook reliability on Clore.ai

Clore.ai servers have dynamic IPs. If your webhooks break after a redeploy:

# 1. Use a static domain with Caddy + Let's Encrypt
# Caddyfile:
# n8n.yourdomain.com {
#     reverse_proxy n8n:5678
# }

# 2. Or use Cloudflare Tunnel (free, no open ports needed):
docker run -d \
  --name cloudflared \
  --network n8n-prod_default \
  cloudflare/cloudflared:latest \
  tunnel --no-autoupdate run \
  --token <your-cloudflare-tunnel-token>

Queue mode for high-volume workflows

# Add Redis and run n8n in queue mode for parallel execution
# Add to docker-compose.yml:
  redis:
    image: redis:7-alpine
    restart: unless-stopped

  n8n-worker:
    image: docker.n8n.io/n8nio/n8n
    command: worker
    depends_on: [redis, postgres]
    environment:
      <<: *n8n-env
      EXECUTIONS_MODE: queue
      QUEUE_BULL_REDIS_HOST: redis

Useful n8n CLI commands

# List all workflows
docker exec n8n n8n list:workflow

# Run a specific workflow manually
docker exec n8n n8n execute --id=<workflow-id>

# Update n8n to latest version
docker pull docker.n8n.io/n8nio/n8n
docker compose up -d n8n

# Check n8n version
docker exec n8n n8n --version

Security hardening

# Run n8n behind a reverse proxy with HTTPS
# Never expose port 5678 directly in production
# Use N8N_BASIC_AUTH or configure SSO via LDAP/SAML

# Restrict which nodes are allowed (whitelist mode):
NODE_FUNCTION_ALLOW_EXTERNAL=axios,lodash
NODES_EXCLUDE='["n8n-nodes-base.executeCommand"]'  # Block shell execution

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Troubleshooting

n8n container exits immediately

docker logs n8n

# Common issues:
# 1. DB connection failed — check Postgres is healthy
docker compose ps postgres

# 2. Encryption key mismatch — if you changed N8N_ENCRYPTION_KEY
#    Credentials become unreadable; re-enter them after key change

# 3. Port conflict
ss -tlnp | grep 5678

Webhooks return 404

# Ensure WEBHOOK_URL matches the public address your webhook senders use
# It must include the trailing slash
WEBHOOK_URL=http://<your-public-ip>:5678/

# Restart n8n after changing this env var
docker compose restart n8n

AI Agent node can't reach Ollama

# Test from within n8n container
docker exec n8n wget -qO- http://ollama:11434/api/tags
# or
docker exec n8n curl http://localhost:11434/api/tags

# If using separate containers not in same Compose network:
# Use host.docker.internal or the server's LAN IP

"ENOSPC: no space left on device"

# Check disk usage
df -h
docker system df

# Prune old execution data in n8n UI:
# Settings → Executions → Delete old executions

# Or set auto-pruning:
EXECUTIONS_DATA_PRUNE=true
EXECUTIONS_DATA_MAX_AGE=72   # 72 hours

Slow workflow execution

# Check CPU usage
top -c

# Enable queue mode for parallel execution (see Tips above)
# Increase Node.js memory if needed:
NODE_OPTIONS=--max-old-space-size=4096

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Further Reading

• n8n Official Documentation

• n8n GitHub Repository

• n8n Self-hosted AI Starter Kit

• n8n Docker Installation Guide

• Running Ollama on Clore.ai

• Clore.ai GPU Comparison

• n8n Community Forum