SPC-10 / Service
MCP server development
The Model Context Protocol (MCP) is the open standard AI assistants and agents use to call tools and read data. We design and build production MCP servers for your APIs, databases and business systems, with authentication, permission scopes, audit logs and rate limits, so AI tools can work with your data without exposing more than they should.
01 / Capabilities
Tool design
We turn your operations into clear, well-described tools and resources that models use reliably.
Security
Authentication, per-user permissions, input validation and protections against prompt injection through tool results.
Operations
Deployment to your cloud, observability on every tool call, versioning and rate limits.
Adoption
Configuration for your teams’ AI assistants and guidance on safe use.
02 / How we deliver it
phase 01
Choose the systems
Pick the data and actions that would save the most time if AI could reach them.
phase 02
Build
An MCP server with a small, safe set of tools, tested with real prompts.
phase 03
Secure and deploy
Authentication, scopes, logging and deployment in your environment.
phase 04
Extend
More tools and systems added as usage grows.
03 / What changes
- AI assistants that can use your real systems
- Access limited to what each user may do
- Every tool call logged and auditable
- One standard instead of many custom plugins
04 / FAQ
Questions about MCP server development.
What is an MCP server?
A small service that exposes your tools and data to AI assistants through the Model Context Protocol, an open standard supported by major AI clients. The assistant can then look things up or take approved actions in your systems.
Is it safe to connect AI to our systems?
It can be, with the right design: authenticated users, narrow tool scopes, read-only by default, approval for actions that change data, and logging of every call.
Which AI tools can use it?
Any client that supports MCP, including Claude, ChatGPT and several coding assistants, as well as agents you build yourself.