Connection design
Define the MCP server, the clients that will use it, and the resources and tools it exposes.
MCP Integration & Model Context Protocol
The Model Context Protocol (MCP) is an open standard that lets AI applications connect to tools and data through MCP servers. Umbrella Tech provides MCP integration for Australian organisations: we design, build and secure MCP servers that expose approved business information and actions to compatible AI clients, so your AI tools can do useful work with controlled identity, permissions and logging.
The problem
The challenge we help you address
Giving an AI application access to business tools creates new trust boundaries. You need to know which servers are trusted, which identity each one uses and what every exposed tool can read or change. Unvetted community servers and broad access tokens make that hard to track.
The outcome
What the engagement should deliver
You gain integrations whose permissions and dependencies are documented and whose owner is named. MCP is assessed alongside conventional APIs as part of our AI Integration work, so the chosen pattern fits the application rather than becoming a requirement by itself. Compatible clients include Microsoft Copilot Studio and a growing number of AI assistants and developer tools.
How we can help
Server engineering
Build MCP servers over your existing APIs and data sources, or assess third-party servers before use.
Access engineering
Implement authentication, authorisation, secret handling and per-tool permissions.
Validation
Test allowed and denied actions, logging, failure behaviour and operational ownership.
Security and governance considerations
An MCP server is a privileged gateway, so we treat it as one: least-privilege access for each tool, no passing user tokens straight through to other services, confirmation for consequential actions and a log of every call. We also design for prompt injection, where untrusted content tries to steer the AI into misusing a tool. Controls align with your Cybersecurity baseline and your AI Governance & Acceptable Use policy.
Frequently asked questions
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What is MCP integration?
It is connecting your systems to AI applications through the Model Context Protocol. An MCP server sits in front of a system and describes the tools and information it offers; a compatible AI client can then use them within the permissions the server enforces.
When should a business use MCP?
When you want several AI tools to reach the same business systems in a consistent way, or when a platform you already use supports MCP. For a single, fixed integration, a direct API connection may be simpler.
Is MCP a replacement for all APIs?
No. MCP can expose capabilities backed by APIs or other systems to compatible clients. Existing APIs, platform support and the trust model determine whether it is useful.
What does implementation include?
Design of the server and its tools, build or configuration, authentication and permission setup, testing of allowed and denied actions, and handover with documentation and monitoring.
How long does an MCP integration take?
It depends on the number of tools exposed, the state of the underlying APIs and the identity and security requirements. We confirm scope and timing during discovery.
Design the connection
Tell us which systems you want your AI tools to reach and what they should be allowed to do, and we will help design the connection.