Agentic systems & MCP servers

An agent is only as good as the tools it can reach. My MCP server development work exposes your data and actions through the Model Context Protocol, safely, with permissions and logs, so Claude and other AI clients can actually do the work. I also build multi-step agents that run on their own, with a human approving what matters.

The problem MCP solves

Most teams use AI by copying text into a chat window and copying the answer back out. It works, but it does not scale, and the model never sees the real state of your system. The Model Context Protocol is an open standard that lets an AI client call tools you define: search your records, read a page, create a draft, update a status. Instead of describing your system to the model, you give it controlled access to it.

What MCP server development looks like in practice

I start by deciding which actions are worth exposing and which should stay manual. Each tool gets a clear name, a strict input schema, and a description the model can understand. Read-only tools come first. Tools that change data get permission checks, sensible limits and an audit log that records who asked for what and when.

I have built this for my own products. Albania Magic, a tourism directory for Albania, has an MCP connector that lets Claude manage places, content and business listings directly. This site runs on WordPress with an MCP server too, which is how its content can be edited from Claude. The same approach works for a Laravel app, a CRM or an internal tool.

For longer jobs, I build agents that plan several steps, call tools, retry on failure and stop for human approval before anything irreversible.

How a project runs

Discovery is a list of the tasks your team repeats and the systems involved. We pick the one with the clearest payoff. I then build the server, test it in Claude Desktop and Claude Code with real prompts, and run evaluations to see where the model misuses a tool. Launch starts with read-only access or a small group of users. After that, support means adding tools as you find new uses, watching costs and tightening guardrails where the logs show a need.

Cost and timeline

Most projects take 3–8 weeks, depending on how many tools are exposed and how much approval logic the agent needs. I give you a written estimate once discovery is done.

FAQ

Which AI clients can use the server?

Claude Desktop, Claude Code and the Claude API support MCP directly, and other clients are adopting the standard. The server itself is not tied to one vendor.

Is it safe to let an AI change our data?

Only with limits. I scope each tool narrowly, check permissions on every call, log everything and require approval for actions that cannot be undone.

Does my WordPress site need to be rebuilt?

No. WordPress can expose MCP tools through the Abilities API and REST endpoints on your existing site.