I build the layer that lets an AI assistant work inside your real systems safely.

An MCP server exposes your CRM, your database, your files or your internal API to Claude as named tools, each scoped to exactly what it may do — read the CRM, never delete from it. Read actions run on their own. Write actions stop and wait for a person to confirm.

On top of that I set up Claude Code in your own repository: an instruction tree and rules committed alongside your code, so the agent follows your conventions in every session rather than being re-explained each time. The dangerous steps are blocked by hooks — code that runs first and can say no — instead of a line in a prompt the model may skip.

Who this is for: teams who already tried a chatbot bolted on top of their data and found it could not actually do anything, or did too much.

How it runs: a short scoping call, then a working server on your staging data in week one, then scope, tests and handoff in week two. You keep everything — the server, the rules and the tests live in your repository.

This is the same architecture I run my own agency on every day.