Service · Data
MCP and data connectors
An agent is only as useful as what it can see. Giving it access to your data is the easy part; giving it exactly the access it should have, and no more, is the work.
What usually goes wrong
- The agent is handed a database credential with full access because it was quicker.
- Nobody can say afterwards which records the agent actually read.
- Every new agent means writing the same connector again, slightly differently.
What we build
- MCP servers that expose your data as tools an agent can use, with the boundary defined in one place.
- Authentication and role-based access, so the agent inherits permissions rather than bypassing them.
- Caching and rate limits, because an agent that loops should not take your database with it.
- A log of what was read and when, which is what turns a security question into a query.
How we build it
Connectors to databases, internal APIs and the SaaS your team already pays for. Written once and reused across agents, so the second agent is much cheaper than the first.
We put AI in almost any business.
- 01
Discovery
We map your processes and data to find where the lost time lives.
- 02
Advisory
We identify what can be automated and what AI actually improves. Judgment, not hype.
- 03
Proposal
We tell you what to do and how, with clear scope, ROI and risks.
- 04
Adoption
We build the agents and integrate them into what you already use.
- 05
Ongoing support
We measure, tune and stay with you as you use it.
Questions we get asked
What is MCP, in plain terms?
A standard way to hand tools and data to an AI model. The value is that it is a standard: you are not writing a bespoke bridge for every model you might use later.
Does my data leave my systems?
Only what a given request needs, and you decide what that is. It is a design decision we make with you, not a default we pick.
Can we use it with agents we build ourselves?
Yes. That is rather the point of using a standard instead of something only we understand.
What data should the agent see?
That question usually takes an hour to answer properly, and answering it is most of the work. Let us do it together.