An assistant becomes far more useful when it can look up a customer, check an order or open the right document.
We build those connections through APIs, existing integrations and, where it fits, the Model Context Protocol (MCP), with explicit limits on what each connection may read or change.
What we deliver
- Integration design and access model
- MCP server development
- Custom API tools for assistants
- Connections to CRMs, databases and document stores
- Read-only access and controlled write operations
- Authentication and permissions
- Usage and activity logging
- Integration documentation
Technology & implementation
MCP is an open protocol that gives compatible AI applications a standard way to reach approved tools and data sources. Instead of building a separate integration for every assistant and every action, a system is exposed once through an MCP server, which declares what it offers (search customers, read an invoice, create a draft). MCP provides the interface; authentication, authorisation and permissions must still be implemented and enforced in the server and the systems behind it.
It is a protocol, not an outcome. It is worth using when several AI tools need the same systems, or when your team works in an AI client that supports it. For one assistant with two lookups, a direct API integration is simpler.
Either way the rules are the same: authentication per user, read-only access by default, write operations limited and logged, and anything read from external content treated as untrusted.
Example use
An illustrative scenario, not a description of a completed project.
An internal assistant retrieves a customer’s order status from an approved system, checks relevant service information and prepares a response.