Matrix42 MCP Server: Ask Your Service Desk in Plain Language
An open-source MCP server that lets Claude, Copilot or Cursor work with Matrix42: the API, the data model and the service desk. Read-only by default.
Alexander Schnabl
Co-Founder, S&S Technologies
Alexander builds the automations at S&S Technologies: n8n workflows, integrations with ITSM systems like Matrix42 and the AI agents that work with them. He wrote the company's open-source Matrix42 node for n8n and the Matrix42 MCP server.
16 articles
GPT-OSS: OpenAI's Open-Source Models That Rival Proprietary LLMs
OpenAI's gpt-oss-120b and gpt-oss-20b are open-weight models you can run yourself. What they mean for AI agents that work without a cloud API.
Machine Learning vs. Generative AI: What SME Leaders Need to Know
Machine learning predicts, generative AI creates. The difference in plain terms and which business tasks suit each in a small or mid-sized company.
What Is Artificial Intelligence? A Plain-English Guide for SME Leaders
A plain-English introduction to artificial intelligence for SME leaders: what it is, where it comes from and where it pays off in daily business.
Prompt Engineering Is Not Enough
Clever prompts make good demos, not reliable processes. What AI in production needs besides: retrieval, fine-tuning and workflows around the model.
LLM Finetuning: LoRA and QLoRA
How LoRA and QLoRA fine-tune large language models with a fraction of the GPU memory and what that means for the cost of custom models.
RAG vs. Finetuning: Choosing the Right Strategy for your LLMs
Retrieval-augmented generation or fine-tuning? When to let a language model look up your data and when to train it, with examples from IT and ERP.
n8n vs Make: Choosing the Right Automation Engine
n8n or Make? A comparison of pricing, GDPR and AI options and why self-hosted n8n with local models can cut costs and latency.
n8n vs. Zapier: Choosing the Right Automation Engine
n8n or Zapier? A comparison of pricing, GDPR, AI costs and hosting and what changes when n8n runs on your own server with Ollama.
Matrix42 Integration in n8n: S&S Technologies' n8n-nodes-matrix42
n8n-nodes-matrix42 connects Matrix42 to n8n: installation, credentials, the operations of the node and an end-to-end example.
Cloud LLM vs Local AI-Agent: Cost Comparison with Real Example
What an invoice-processing agent costs with a cloud LLM API and with a small model on your own GPU, calculated on a real workflow.
The Cost of Doing Nothing: Hidden Inefficiencies in Legacy Workflows
Copying data between ERP and spreadsheets by hand costs more than it seems. Where the hidden costs are and how automation with n8n removes them.
Small Language Models (SLMs): Agentic AI for Your Workflow Automation
Most AI agent tasks run well on models under 10 billion parameters. Why small language models on Ollama and n8n cut costs and keep data in-house.
Internal Knowledge Bases with RAG: Architecture, Tools and Maintenance
How to turn PDFs and documents into a chat that answers with sources: ingestion, embeddings, vector store and upkeep of a RAG knowledge base.
GDPR & AI: Safe Local Hosting for LLMs
Why cloud LLMs are a GDPR risk for European companies and how running language models locally keeps data, costs and latency under control.
How to Run LLMs Locally
Step by step: choose a model, check your hardware, install Ollama and connect it to n8n to run language models on your own machines.