Specialist engineering

Custom MCP Server Development

Give AI applications a controlled way to work with your business systems through the Model Context Protocol.

THE RIGHT SCOPE. CLEAR BOUNDARIES.

Practical engineering
for the work ahead.

ORVIAN designs and builds custom Model Context Protocol servers for organizations connecting AI applications to internal tools, APIs, and operational data. We start with the work an assistant needs to perform, the identity behind each request, and the systems that remain responsible for the data.

An MCP server provides a standard interface for defined capabilities. It does not replace your source systems, make every action safe by default, or supply an entire agent platform. We design the surrounding authorization, orchestration, and approval controls according to the use case.

The result is a bounded integration your team can inspect and operate: explicit tool contracts, predictable responses, secure credential handling, and documented behavior when an upstream system fails. If a direct API integration is the simpler fit, we explain that during discovery.

WHAT THE ENGAGEMENT CAN INCLUDE

Defined deliverables.
Operational detail.

We agree the scope and acceptance
criteria before implementation.

01

MCP architecture and capability design

Define the compatible clients, source systems, tools, resources, and deployment boundaries. Separate retrieval from actions and document which operations require human approval.

02

Custom server implementation

Build focused tools with validated inputs, structured outputs, useful errors, timeouts, and clear execution limits. Expose the business operations the application needs rather than an unrestricted backend interface.

03

Authentication and authorization

Design client and user identity flows, OAuth where appropriate, and scope enforcement. Preserve the source system’s record permissions and tenant boundaries at execution time.

04

Enterprise API connections

Connect approved APIs, databases, and business platforms. Keep downstream credentials on the server and define how to handle pagination, dependency failures, and upstream rate limits.

05

Testing and operational visibility

Test permission boundaries, malformed requests, unavailable dependencies, and recovery behavior. Add tracing and audit records that are useful without exposing sensitive credentials or unnecessary data.

06

Deployment and handover

Prepare environment configuration, secret management, release checks, runbooks, and ownership. Agree on maintenance and compatibility support before the server becomes an operational dependency.

CONTROLS THAT BELONG IN THE DESIGN

Built to be understood,
operated, and maintained.

Security, recovery, and ownership are part of the engineering scope. We define the boundaries before connecting systems or changing workflows.

  • Least-privilege access to downstream systems
  • Validated tool inputs and bounded actions
  • Per-user and tenant-aware authorization
  • Explicit handling of untrusted tool output
  • Auditable execution and revocation paths
  • Approval gates for consequential operations

HOW WE APPROACH THE WORK

From discovery
to dependable operation.

01

Map the use case

Identify the users, business operations, data sources, and success measures. Confirm whether MCP adds useful interoperability.

02

Define the boundaries

Agree on permitted tools, identity flows, read and write scopes, and any human approval points.

03

Implement and evaluate

Build the integration and test it against realistic workflows, access restrictions, and failure conditions.

04

Release and operate

Deploy with monitoring, documented recovery, and a clear process for changing capabilities and permissions.

PART OF A CONNECTED ENGINEERING PRACTICE

Enterprise AI & Integrations

This engagement sits within ORVIAN’s broader engineering capabilities. Explore the related service to see how it connects to your wider architecture and operational needs.

Explore Enterprise AI & Integrations

GOOD QUESTIONS

A little more clarity.

Every environment is different.
Let’s talk through yours.

Start a conversation
What is a custom MCP server?

It is a service that exposes a defined set of tools and data through the Model Context Protocol. Compatible AI applications can discover those capabilities and call them through a consistent interface. The server connects those requests to the systems your organization already uses.

Can an MCP server create or update records?

Yes, when the agreed scope and source-system permissions allow it. We separate retrieval from changes, validate each action, and use approval gates where needed. A request from an AI application does not replace authorization.

Can the integration stay in our environment?

We assess your hosting, networking, identity, and data-handling requirements during architecture design. Deployment can be designed around your approved environment and operating responsibilities rather than assuming that internal data must move to a shared application.

How do we start an MCP development engagement?

Bring a workflow, the systems involved, and the AI applications you want to support. We use discovery to define a first bounded capability, evaluate its security and operational requirements, and agree on scope and acceptance criteria before implementation.

FOCUSED ENGINEERING SERVICES

A clear starting point
for a specific challenge.

Explore the scope, approach, and controls
behind a focused engagement.

YOUR NEXT CHAPTER, ENGINEERED.

Start with a focused conversation.

Share the workflow, systems, and constraints. We’ll help define a useful scope, the controls it needs, and a practical path to implementation.

Discuss an MCP Integration