Steps to build a custom MCP server for your business systems
The five steps to connect an AI assistant to your own systems through a governed MCP server, from the tool list to a staging test with a real assistant.
Written by Cameron Young, CEO · Reviewed by Tara Buckley, COO on
- AI and automation
- MCP servers and agent access
Quick answer:A custom MCP server is built by mapping tools, scoping authentication, validating inputs, adding rate limits and logging, then testing with a real assistant.
Quick answer
How is a custom MCP server built?
A custom MCP server is built by mapping the tools an assistant needs, scoping authentication, validating inputs, adding rate limits and logging, then testing with a real assistant before go-live.
Additional Context
Each step keeps the assistant inside the permissions a staff member already holds in the source system.
Sources
- Annual Cyber Threat Report 2024-2025
Average self-reported cost of cybercrime per report for Australian businesses: $80,850 (FY2024-25).
Model Context Protocol
Before the steps
The sequence below is the one a business typically follows to connect an AI assistant to its own systems. The page on MCP servers and agent access explains what an MCP server does and how it is secured once the systems are exposed. Assistants that act on a customer's behalf are covered under AI agents, and the AI Automation Assessment is the fixed-fee starting point for a first build.
Step-by-step
Steps to build a custom MCP server
Varies with the number of systems connectedAdvanced
The sequence a business typically follows to connect an AI assistant to its own systems through a governed MCP server.
Supplies Needed
- Documentation for each system being connected
- A list of required tools and the permissions each one needs
Tools Required
- MCP SDK
- OAuth 2.1 authorisation server
- API gateway or reverse proxy
- Logging and monitoring stack
Steps
- Map the tools a business actually needs
List the specific lookups and actions an assistant should perform, such as checking stock or raising a ticket, rather than exposing a whole database.
- Design authentication and scopes
Set up authentication that matches each caller to the same permissions they already hold in the source system, not a shared service account.
- Build typed tools with validation
Define each tool's inputs and outputs so the assistant gets a structured answer or a structured error, never a raw database dump.
- Add rate limits and logging
Cap how often each tool can be called and log every request, so an unusual pattern of calls is visible before it becomes an incident.
- Test with a real assistant before go-live
Connect the server to Claude or ChatGPT in staging and run realistic queries, checking every answer cites the data it came from.
Summary: A custom MCP server is built by mapping tools, scoping authentication, validating inputs, adding rate limits and logging, then testing with a real assistant.
Ready to connect your systems to an AI assistant properly?
National Digital scopes, builds and operates MCP servers so an assistant like Claude or ChatGPT can query your systems through typed tools, with authentication and logging built in from the start.
References
- Australian Signals Directorate. (2025). Annual cyber threat report 2024-2025. https://www.cyber.gov.au/about-us/view-all-content/reports-and-statistics/annual-cyber-threat-report-2024-2025