The integration layer
Increasingly this work is expressed through MCP, the Model Context Protocol — a standard way for AI applications to reach external data, tools and workflows. Build the capability once and it becomes available across compatible models and harnesses.
MCP does not remove the work. Someone still implements the server, the authentication, the permissions, the error handling and the mapping to the underlying system. What it removes is doing that again for every model you try.
MCP servers
Your systems exposed as governed capabilities an agent can reach.
Data and RAG pipelines
Retrieval grounded in your own knowledge, refreshed as sources change.
Identity and permissions
Role-aware access enforced in the system, not in the prompt.
Done properly
Permissions enforced before retrieval or tool execution, not suggested to the model in a prompt. Least-privilege identities per agent. Audit trails on actions that matter. A bad release that is detectable and reversible.
Build Your Organisation’s AI Capability
Start with a focused AI Discovery Sprint. We will map your use case, organisational knowledge, systems, MCP integrations, security requirements and delivery architecture.