Developers should begin here because these first steps take place in Visual Studio Code using the RASON Desktop extension. This section shows how to open the extension, load an example RASON model, and review the model before solving or exporting it. End users or runtime users who only need to run an already exported model in Power BI or Excel can skip ahead to the runtime user starting point, where the walkthrough explains how to use RASON Runner from the External Tools menu in Power BI or the RASON tab in Excel.
Step 1: Open Visual Studio Code
Launch Visual Studio Code and the RASON Desktop Extension by clicking on the left menu bar. Refer to the previous chapter for details on the purpose and function of each section of the extension.
Figure 1: Visual Studio Code with the RASON Desktop extension open.
Step 2: Open the RASON Example
Users can open an existing RASON model, pick one from the Examples side bar or insert a starter with RASON: Insert Templates in the command palette. This example opens the ProductMix4.json example RASON Optimization model.
Under Examples, click Optimization – Linear Optimization – ProductMix4.json to open the Product Mix RASON Example model. This model determines the optimal production quantities for three products, TVs, Stereos and Speakers, by maximizing total profit subject to parts inventory constraints. Decision variables represent the quantity of each product to produce, while constraints enforce limits on available parts inventory. The objective function selects the combination of production levels that yields the highest profit while satisfying all constraints.
Notice the use of the finalValue:[] property under “variables” and “objective” sections. This property sends the final values for each to the results. The results for this example will contain the final values for the objective and the variables. Results are output to a dataframe which can be viewed in the Dataframe viewer, as described below.
Figure 2: Product mix example model open in Visual Studio Code, showing the RASON model ready for execution.
Step 3: Use MCP Server to become a RASON Expert
RASON Desktop includes the RASON MCP Server, giving GitHub Copilot Chat full access to RASON's modeling, analysis, and solving capabilities. The server includes a searchable library of nearly 200 example models, templates that guide model generation, structural analysis, and Solver result interpretation, all available immediately. For example, to gain help with adding a new product, say a gaming console. to the existing Product Mix example, simply type: How would I add a new product, Gaming Console, to the existing ProductMix4.json example?
Figure 3: Frontline's MCP Server gives you a Copilot "RASON Expert"
This screenshot shows the RASON MCP Server’s response which identifies the JSON sections that must be updated and lists the required changes, including increasing the product dimension from 3 to 4, adding a new profit value, and updating the parts data to account for the additional product. It provides a step-by-step guide for modifying the model structure directly from the chat. For more information on Frontline’s MCP Server, see the previous chapter.
Next: Run the Model and Review Results
Continue to the next page to run the ProductMix4 model in RASON Desktop, review the solver output, and open the results dataframe.