Tool and access design
A scoped set of tools, input contracts, authorization rules, and intended client workflows.
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MCP Integration Sprint
Put your business tools within AI’s reach.
Give your AI assistants a controlled connection to one business system. A documented MCP interface, tested tools, and the access boundaries your workflow needs.
Teams connecting AI assistants to internal systems
Sound familiar?
Every assistant needs a different one-off integration.
Your data is accessible but business actions are difficult to control.
You want reusable tools that can be tested and maintained.
What you take away
Deliverables you
can actually use.
The starting package covers one business system and up to five agreed mcp tools. We confirm the exact boundary together.
Working MCP server
An implementation connected to the agreed API or data system, with clear errors and bounded operations.
Validation harness
Tests for the scoped tool behavior, permission boundaries, and representative failure cases.
Deployment and client guide
Deployment instructions, client configuration examples, and a handover session.
A practical guide
Give an assistant a clear contract with your system.
A useful MCP integration exposes a small set of business operations an assistant can understand and a system can enforce. MCP stands for Model Context Protocol. Start with one workflow and decide exactly which information and actions the assistant needs.
How to do it yourself
First, describe the intended assistant workflow in ordinary language. Separate reading information from changing it. Choose a small set of operations with clear names and business meaning, such as finding an order or preparing a request. Keep the scope tied to the workflow you want to support.
Define the input and result for each operation. Include required fields, allowed values, identifiers, and understandable error outcomes. Decide how the user’s identity and permissions will be checked by the server. The tool description should explain its purpose, while the implementation enforces its boundaries.
Connect the operations to a test system and exercise them directly before involving a model. Check valid input, missing data, denied access, and unavailable dependencies. For an operation that changes state, decide how repeated requests are recognized and what confirmation the workflow needs.
Then try the integration with the intended client. Observe whether the assistant selects the right tool and supplies meaningful arguments. Treat returned documents and records as data, even when their text looks like instructions. Keep access limited to the operation the user actually requested.
Finish with a documented configuration and a set of repeatable examples. Make errors and execution records useful to the person supporting the integration. Recheck client compatibility and authorization behavior when the server or client changes.
How we approach the work
Our plan combines practical AI workflows with API design, .NET services, and domain modeling. We design tools around business responsibilities rather than exposing database internals. That keeps the assistant’s available actions understandable and helps the underlying application retain ownership of its rules.
We agree the target clients and access model, implement the bounded tools, and test the behavior through both direct calls and representative assistant workflows. The handover includes the contract, configuration examples, failure cases, and maintenance guidance for the system owner.
The tools behind the work
The MCP Inspector helps inspect and exercise the server interface. The existing business API remains the source of its domain behavior; a .NET implementation is appropriate where it fits the application. Automated checks cover the tool contract, access boundaries, repeated calls, and failure handling.
We use SDD, Specs Driven Development, to link the intended assistant workflow to tool specifications and acceptance tests. SDD’s own MCP interface also provides a practical context for this way of working: business intent, implementation tasks, and validation evidence remain connected.
Explore the tools
Ready to begin
What we need
from your team.
- A documented API or an agreed data-access path
- Authorized test credentials for the target system
- The intended clients and their access model
A few useful answers
Before we start.
Can a tool change business data?
Yes, when explicitly scoped. Write operations require appropriate authorization, input validation, and confirmation or review points. Read-only tools are a useful first slice.
How is the engagement priced?
The indicative estimate starts at €6,500, excluding VAT, for the stated package boundary. After a fit conversation, you receive a fixed quote with the exact deliverables, fee, and schedule. Work starts after acceptance; changes are quoted separately.
What happens after delivery?
You receive the working files, findings, and a handover session. Your team can take the next steps, or we can scope a follow-on engagement together.
Let’s talk about MCP Integration Sprint
Your next step
starts here.
Tell us what needs to change.
We’ll review your request and come back with a practical next step. No commitment required.
Prefer email? dev@roggemans.com ↗Discuss this package
A little context helps us make the conversation useful.
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