Custom MCP server development, so AI agents can work in your systems under your rules

Your assistant starts doing work in your systems, and people stay in charge of every change that matters. Instead of copying an order number from the chat into the ERP, checking a customer's history in the CRM by hand or filing a document in the DMS, staff ask the assistant, check what it prepared and approve it. Reading comes first. Writing is added one action at a time once reading is reliable.

• Less copying between systems: the assistant looks up and prepares, people approve
• Faster answers to customers, because order, ticket and contract data are one question away
• Your existing access rules apply, so an agent sees only what the person it works for may see
• Every call logged, so IT and auditors can see what happened
• One standard connection per system that several AI clients can use, instead of a separate integration for each

Suppose your support team wants its assistant to look up a customer's open tickets and draft a status update. An MCP server could offer two tools. One reads ticket details through your helpdesk API with the access rights of the person asking. The other prepares the update and posts nothing until that person has approved the text.

First we check whether you need an MCP server at all. Your assistant may already have a connector for the system, or an ordinary API integration may be simpler, and then we recommend that instead. When a server is the right choice, the first commission is one bounded tool, such as reading an order, built for the client your team actually uses.

We begin with read-only tools and the narrowest scopes the task allows. Where the underlying system supports it, a call runs as the user who asked, so your existing access rules apply. Any tool that changes data first asks a person for explicit approval.

Internal APIs time out, hit rate limits and sometimes fail halfway. Each tool gets timeouts and retry rules that respect the API behind it. Not every API makes repeated writes safe on its own, so we design each write operation to be idempotent: a retried call does not repeat the business action or post the same update twice.

Whether the server runs locally next to the client or as a remote service in your environment is decided after we have reviewed access and security with your team.