EXPLORE THE WORKFLOW
From an agent request to a business tool.
1. Your AI agent
A compatible AI application contains an MCP client that can discover the tools a server exposes. For example, a user asks it to retrieve the status of an approved production work order.
2. Custom MCP server
The server presents a defined tool, such as looking up one work order. The implementation checks identity, permitted scope, and input values before handing work to the underlying connection.
3. API or RPA connection
The integration uses a supported API, approved data access, or a narrowly scoped RPA procedure. It should enforce the same business limits regardless of which agent requested the action.
4. Your business system
The authorised operation runs in the source application. Its response is checked and returned with enough context for the agent to explain the outcome, including errors or incomplete results.
Step 1 of 4
A permitted requestReturn only the information or result the caller may access.
Outside the agreed scopeReject the request or route it for the required review.
Agent, MCP server, and business software
The agent helps interpret the user’s request. The MCP server exposes a defined set of capabilities. The existing business application remains the system that holds records and enforces its own rules.
The official MCP architecture distinguishes the AI host, its clients, and connected servers. This separation is useful when deciding where identity, tool permissions, and execution checks belong. A language model on its own is not an MCP client.
Example: ask about a production work order
A production planner might ask an agent, “What is the status of work order WO104?” A scoped tool could accept the work-order identifier, check the planner’s permitted site and records, and return its status from the connected system.
Looking up a work order and changing it should be separate capabilities. If changing its planned quantity requires approval, the integration should enforce that requirement before modifying the record. A prompt asking the agent to “be careful” is not an access-control mechanism.
Can it work with an agent you already have?
Potentially, if that application supports compatible MCP connections and the features the integration needs. The client and server must agree on supported capabilities. Sign-in methods, connection types, and available tools can differ between AI products.
We check the chosen agent before committing to a design. BYMTECH can build the MCP connection for a customer’s compatible agent, for an agent we develop, or for multiple supported clients. Reusing tools can reduce duplicated integration work, but each client still needs testing.
Where RPA fits
An MCP server does not require RPA. It can use an API or another approved connection. If suitable older software has no direct interface for the required operation, a defined RPA workflow may sit behind a custom tool.
The agent requests the business operation; the integration controls how it is executed. Screen changes and session failures still need handling in the RPA component. Calling that component through MCP does not remove those limitations.
Start with a small set of well-defined tools
- Keep scope explicit: specify the accessible records and permitted operations.
- Separate reading and changing: grant only the capabilities needed by each role.
- Validate requests: check inputs and business rules before execution.
- Make outcomes traceable: record requests, approvals, and results with suitable access and retention controls.
The MCP tools specification recommends user visibility and human control over tool invocation. The final design should make those controls effective in the agent and the integration.
Further reading
Official references for the concepts in this guide. The workflow examples are illustrative; the design for your business depends on its systems, access, and operating requirements.