Prototypr.ai MCP Documentation

Welcome to the prototypr.ai MCP docs! This section will provide you with in depth information and guidance about how to use the new prototypr.ai MCP server.

What is Model Context Protocol?

Model Context Protocol (MCP) establishes an open standard for connecting applications with Large Language Models (LLMs). It provides a consistent way for software to surface functionality and context as structured tools, enabling LLMs to move beyond static responses and engage directly with application workflows. By aligning on MCP, developers can ensure their tools are broadly compatible with AI assistants across different platforms without requiring vendor-specific integrations.

If you would like to learn more about MCP, the benefits, how MCP servers are different from a traditional API, then please check out prototypr.ai's guide on How to Build an MCP Server.

What is the prototypr.ai MCP Server?

The prototypr.ai MCP Server is a premium feature currently in Beta and free to try for developers. The tools are currently focused on helping you search and import designs directly in your code editor. There are currently four tools available:

• search_workspace_designs: Search for designs in your prototypr.ai workspace and return a list of designs by id.
• get_code_for_workspace_design: Import Code from your prototypr.ai workspace for a particular design by id.
• search_community_marketplace_designs: Search for designs in the prototoypr.ai community marketplace.
• get_code_for_marketplace_design: Import Code for a particular design from the prototoypr.ai community marketplace by id.

More MCP Tools are coming soon!

How to install prototypr.ai MCP Tools

Let's walkthrough how to integrate prototypr.ai's MCP tools with your MCP client.

The first thing that you need to do is to login and navigate to /home > /api-keys and generate a prototypr.ai API Key.

With your API key in hand, you can either copy and paste the following mcp object and manually add it to your client's mcp.json file.

                            
{
  "mcpServers": {
    "prototypr": {
      "url": "https://www.prototypr.ai/mcp",
      "displayName": "Prototypr AI",
      "description": "Prototypr.ai is a research platform that helps people build, measure and learn faster with leading LLMs.",
      "icon": "https://www.prototypr.ai/static/img/ai_icon_32x32.png",
      "headers": {
        "Authorization": "Bearer INSERT_PROTOTYPR_AI_API_KEY",
        "X-User-Id": "INSERT_USER_ID",
        "X-Workspace-Id": "INSERT_WORKSPACE_ID"
      },
      "transport": "stdio"
    }
  }
}
                            
                        

Prototypr.ai Cursor Integration

The other option to install prototypr.ai MCP is to click on the Add To Cursor Button. This will trigger your browser to open a deeplink into Cursor and install it. You can find the Add to Cursor Button in the /api-keys page or when viewing code for any design in prototypr.ai Studio.

MCP Guides

If you are interested in building your own MCP server in python, prototypr.ai has put together a handy post to help you get started. Check it out at the link below.

How to Build a MCP Server - A Practical Guide for Developers

Get started with building a simple MCP server in python that can act as a bridge between systems.

MCP FAQ