MCP SERVERS
One standard connection between AI and your tools.
MCP is an open protocol that standardizes how AI models reach enterprise tools and data. It ends the habit of writing a fresh integration for every model.
What MCP is — and is not
- What it is Model Context Protocol: a standard way to offer tools, data sources and prepared prompts to an AI model. It does for AI-to-system connections what USB did for devices.
- What an MCP server does It publishes one capability of your organization — look up an order, update stock, search documents — as protocol-compliant tools. Swap the model and the server stays.
- What it is not Not a model, not an agent, not a database. It adds no new intelligence; it lets existing intelligence reach your systems safely.
- Why it matters Three models across five systems is fifteen bespoke integrations the old way. With MCP you write five servers, and all three models use them.
- Where security lives The server is the enforcement point: authentication, role-based tool access, input validation, rate limits and full request logging all sit here.
MCPTOOLS / RESOURCES / PROMPTSSTDIO & HTTPOAUTH 2.1ROLE-BASED ACCESSREQUEST LOGGINGTYPESCRIPT / PYTHON
When you need an MCP server
- You want several AI clients — assistants, agents, internal apps — hitting the same enterprise systems
- You need one place to govern what AI can read and do, and to prove it afterwards
- You want integrations that survive a change of model provider
- You need to expose legacy systems to AI without rewriting them
How we work
- 01 Inventory Which system, which operation, which data. We draft the tool surface together.
- 02 Contract design Every tool gets an input/output schema, defined error behaviour and an access rule.
- 03 Build We write and test the server; it runs inside your network or on your own infrastructure.
- 04 Wiring Connected to your agents and AI clients, validated against real scenarios.
- 05 Operation Versioning, monitoring, new tools over time — with contracts kept stable as it grows.
Frequently asked
Does an MCP server send our data outside?
No. It runs on your infrastructure and returns only what the defined tools return. Paired with an on-premises AI server system, the whole chain stays inside the organization.
We already have APIs. Why another layer?
Your APIs were designed for people and applications. An MCP server makes the same capabilities legible to a model: precise descriptions, strict schemas, narrow scopes and a single point of audit.
Which clients does it work with?
Any MCP-capable AI client, plus the agents we build. Because the protocol is open, the server stays independent of whichever model you run today.
Get the connection layer right and production follows.
No deck needed. 20 minutes. The rest is up to you.