Chat answers are easy. Getting an AI model to safely read your database, call your internal APIs or act inside your tools takes real integration work. For 10+ years we've placed engineers with 70+ businesses — now including developers who build Model Context Protocol servers that connect your systems to AI the right way.
These are the problems teams hit trying to wire AI into their stack.
Your AI is stuck answering questions instead of doing real work in your systems.
Custom integration glue code breaks every time a model or API changes.
You're wary of giving an AI model uncontrolled access to production data.
Almost no one on the market has real MCP experience yet — it's brand new.
Every new AI feature request means re-building the same connections from scratch.
A poorly scoped integration is a security incident waiting to happen.
MCP is quickly becoming the standard way AI models talk to real tools and data. We place engineers who build these integrations securely, once, the right way.
If your AI needs to act, not just answer, this is for you.
You need your assistant to actually query internal data or trigger workflows, not just chat.
You need AI access to systems scoped, permissioned and auditable — not a wide-open API key.
You want a standardized integration layer once, instead of custom code per AI feature.
Each problem above maps to how we staff. Here's how we fix it.
We build MCP servers that let models safely query data and trigger real actions in your stack.
Tight permissioning and audit trails, so the AI can only do exactly what you allow.
We build MCP integrations for our own products, so our engineers bring hands-on experience, not slideware.
One well-built MCP layer serves every future AI feature instead of one-off integrations.
We shortlist from an existing pool of pre-vetted candidates, so you interview in days, not months.
Access scoping and review are part of the build, not bolted on after something goes wrong.
This is a new discipline with very little real-world track record on the market. Our engineers have built and shipped MCP servers on our own projects, so when we place someone, they've already solved the security and reliability problems your integration will hit. For 10+ years and 70+ clients, that's our standard.
Book a Talent Call →The same integration, three very different risk levels.
We scope which systems need connecting and to what depth — no cost, no obligation.
We shortlist engineers with real MCP build experience.
They design the server, scope access and add auditing from day one.
The same layer powers your next AI feature without starting over.
CrecenTech's developers deliver high-quality code with the right level of oversight. Fully satisfied with our collaboration.
They build MCP servers that expose your internal tools, APIs and data sources to AI models in a standardized, secure way — so agents can safely read and act on your systems instead of relying on brittle custom glue code.
Security is the core of the job. We place developers who scope access tightly, add auditing and permissioning, and design integrations so the AI can only do what you explicitly allow.
No. Many clients start with one well-scoped integration — like connecting a support tool or internal database — to prove value before expanding further.
We match from an existing vetted pool, so you're typically interviewing within days and can have someone contributing shortly after.
Both. Many clients start on contract to prove fit on real work, then convert strong performers to permanent.
Book a talent call — we'll scope your integration and match an engineer with real MCP experience.