Solution · AI MCPs

Let AI act on your business — safely.

The next wave of AI doesn't just answer — it acts. Model Context Protocol (MCP) servers turn the systems you already own into safe, governed tools for AI agents — no rebuild required. Wrap once; any assistant works under your governance and your audit log.

The challenge

AI can talk but can't act.

Your assistants can summarize, draft and answer — but the moment something should happen, a person copies the answer into the real system. Every pilot ends at the same wall: the AI has no safe way to touch the systems where work actually happens.

Pointing an agent at raw APIs isn't the answer — no permissions, no audit trail, no way to explain later what acted on what.

Our approach

Wrap your systems as governed tools.

We wrap the systems you already own — ERP, CRM, core platforms — as MCP servers: curated tools with permissions, validation and logging built in. No rebuild of what already works.

Wrap once, and any approved agent — Claude, Copilot, Foundry — can work with them under one governance model. Every action permissioned, logged and reversible.

What it buys you

Your existing applications become AI-ready in weeks, not years. One wrapping unlocks every AI agent — internal, partner, vendor — without re-integration. Governance and audit move from a per-agent problem to a per-tool problem, with one source of truth for who can do what.

When to start

Mid to late maturity. Becomes essential the moment you have more than one AI agent or more than one team building agents — that's when shared MCPs stop the chaos and prevent duplicated, ungoverned integrations.

Use cases & how we solve them

Where this lands in practice. Each row opens with the detail — and what it buys you.

01

App MCP servers for your existing systems

Wrap SaaS and internal applications (CRM, ERP, ticketing, billing, support) with MCP servers so AI agents can call them through a curated set of tools and actions — instead of being pointed at raw APIs.

  • A curated set of tools and actions per system — not a raw API dump
  • Permissions, rate limits and input validation enforced at the MCP layer
  • Works with the agent platforms you already use — Claude, Copilot, Foundry

The payoff. Every system you own becomes AI-usable without a single rebuild.

02

Governed data MCPs over the lakehouse

Expose data products from the lakehouse and semantic layer through MCP so agents query under the same governance, row-level security and audit log that human users do.

  • Agents query through the same semantic layer, row-level security and audit log as humans
  • Data products exposed deliberately — schema, definitions and freshness included
  • Every agent query logged and attributable

The payoff. AI answers from the same governed numbers the board reads.

03

Action & write-back MCPs with guardrails

Curated write operations — create a ticket, queue an approval, draft an email, propose a refund — exposed as MCP tools with policy guardrails and human-in-the-loop where it matters.

  • Write operations curated one by one — create, queue, draft, propose — never blanket access
  • Policy guardrails decide what runs straight through and what waits for a human
  • Every action logged, attributable and reversible

The payoff. Agents that do real work, with the blast radius designed out.

04

Multi-agent MCP catalogue

A registry of MCPs across business functions — any agent on any platform (Claude, Copilot, Foundry) can discover and use them under shared governance. Stops every team from inventing its own integration.

  • One registry of MCP tools across business functions, discoverable by any approved agent
  • Shared governance: one access model, one audit trail, one place to switch things off
  • New agents onboard in days, because the integrations already exist

The payoff. Ten teams adopting AI without inventing ten integration stacks.

05

Legacy-system MCP enablement

Bring older systems — SQL Server, mainframe-fronted APIs, file shares, internal portals — into the agent ecosystem through adapters, without rewriting the systems themselves.

  • Adapters bring SQL Server, file shares and internal portals into the agent ecosystem
  • The legacy system stays untouched — the adapter carries the safety rails
  • Same governance and logging as the modern stack

The payoff. The systems too old to change join the AI era anyway.

How we deliver it

Through the Moberg Delivery Framework — the same five stages, governance and engineering standards we run on every engagement, from business case to long-term run. Microsoft has independently validated the AI practice underneath — but judge us on a catalogue of governed tools your agents can't misuse.

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