Give your AI agent safe access to your real business systems
An agent that cannot reach the systems a business already runs is a chat window. Most teams stall exactly here, because giving a model real access safely is a different problem from prompting it well. This covers Model Context Protocol end to end. Typed tools instead of scraped screens, read paths kept separate from anything destructive, credentials verified before a single write, and the failure modes that only show up in production. Built on open source MCP servers I publish for infrastructure, ERP, marketplace and booking platforms. The code is readable on GitHub before we start.
What's included
Three to four sessions. We pick one system your agent needs to reach, design the tool surface together, build the server live, then test it against the cases that actually break things, a bad credential, a timeout, a malformed response.
- One MCP server exposing your own system to an agent, running locally on your machine
- A safety model that keeps read paths separate from anything that can destroy data
Meet your expert
Mirza I.
Production AI Is a Different Problem (AI & ML Engineering)
Writing software full time since 2011, alongside a BSc and then a Master's at the University of Passau. Enterprise delivery in Germany and the UK since 2018. No shortcuts, no straight line. A genuine obsession with technology, how it works, and what it can do for people when it is set up properly. That path led through enterprise consulting, AI systems, and eventually Frankfurt, where the focus now is on what is coming next. Agents, large language models, and the infrastructure that makes them run in production rather than in a demo. Certified n8n Expert Partner, licence 18628384, valid through February 2028, with code merged into n8n core. I deliver automation and integration work across banking, telecommunications, public sector and manufacturing in the DACH region. The kind that still runs after the engagement ends, rather than a half-finished workflow.
