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How to create Roadmap Prioritizer using MCP

Score and rank features using RICE or MoSCoW. This guide creates the Roadmap Prioritizer prompt from Arthur's template catalog, sets up a blank MCP server, and links the prompt so any connected AI client can use it.

Steps

  1. Go to Prompt Templates and search for Roadmap Prioritizer.

    Open the Prompt Templates catalog

    Search the catalog for the Roadmap Prioritizer template

  2. Click Use template on the Roadmap Prioritizer card and review the prefilled name, description, and content preview.

    Open the Roadmap Prioritizer template with its prefilled name and content preview

  3. Click Create prompt — the prompt is added to your shared library.

    Create the Roadmap Prioritizer prompt in the shared library

    Start creating the MCP server that will expose the prompt

  4. Go to New server, choose Blank / Static as the source, and click Next.

    Choose the Blank / Static source — no external connection is needed for a prompt-only server

    Advance to the server details step

    Name the server after the prompt it will expose

    Create the blank MCP server

    Open the server's Prompts tab

  5. Name the server (for example, Roadmap Prioritizer Server) and click Create server.

    Open the prompt-library picker

  6. On the server's Prompts tab, click Add prompt, search for Roadmap Prioritizer, and click Add.

    Search the library for the Roadmap Prioritizer prompt

    Link the Roadmap Prioritizer prompt to the server

    Close the picker and show the linked prompt on the Prompts tab

  7. Open the server's Connect section and click Share the MCP swagger documentation — Arthur generates the public documentation link and QR code for this server.

    Open the server's Connect section, where the MCP endpoint and its documentation live

    Open the MCP swagger documentation share panel

    Show the generated swagger documentation link and QR code for this server

Confirm it worked

The Roadmap Prioritizer prompt appears on the server's Prompts tab, and the Connect section offers the server's MCP swagger documentation — a shareable page with setup instructions for any AI client. A connected client can now fetch the prompt through this server.

Good to know

  • Evaluates a list of features using prioritization frameworks to produce a ranked roadmap.
  • Arguments detected from the template: {{product}}, {{team}}, {{timeframe}}, {{goals}}, {{framework}}, {{features}} — callers fill these in when invoking the prompt.
  • Editing the prompt in the shared library updates it on every server where it's linked.

Related

Tutorial video