MCP Servers
Connect AI agents to your systems under control – with sign-in, clear permissions and traceable access.
dectria builds MCP servers through which AI applications such as Claude, ChatGPT, Microsoft Copilot Studio or your own agents access your systems: reading data, finding documents, creating records. Every access runs through defined tools, with sign-in and the permissions of the respective user.
We run MCP in production ourselves: via MCP, Claude or your own agents can connect securely to NetCero, an ESG platform in which dectria holds a stake. Access is secured with OAuth and role-based permissions.
We start with a few narrowly scoped tools and only expand once it is clear how agents actually use them.
Official website
Your contact Michael Jauk Contact for AI & data What is MCP – and when is it worth it?
The Model Context Protocol (MCP) is an open standard through which AI applications access external data and functions. An MCP server provides tools, resources and prompts that any MCP-capable AI application can use without its own integration.
MCP is worth it when several AI applications or agents need to access the same systems, or when users want to work with company data directly in their AI assistant. It is not worth it when a fixed process should always run the same way – a classic interface is more predictable there. And if agents would write to critical systems, you first need human approval, not more tools.
MCP or classic API integration?
| MCP server | Classic API integration | |
|---|---|---|
| Who decides on the call | the model, based on the tool description | hard-coded logic |
| Connecting a new AI application | no extra effort if it supports MCP | separate integration per application |
| Security | OAuth 2.1, permissions per tool | API keys or OAuth, depending on the system |
| Predictability | lower – approval needed for critical steps | high |
| Suited for | assistants and agents with open-ended tasks | fixed, recurring processes |
Related topics
Capabilities
What We Build with MCP
Use Cases
Typical Use Cases
AI Access to Company Data
Employees ask their AI assistant about customers, orders or documents – the MCP server returns only what that person may see.
Agents for Recurring Tasks
Agents create tickets, prepare reports or reconcile data; critical steps go to a person for approval first.
Making Legacy Systems AI-Ready
For systems without a ready-made connector, the MCP server becomes the adapter – with narrowly scoped tools instead of direct database access.
FAQ
MCP FAQ
What is an MCP server?
How is an MCP server secured?
Which AI applications support MCP?
Does MCP work for legacy systems without an API?
What is Code Mode in MCP?
Every project starts with a conversation.