Best Visual MCP Server
Builder in 2026

*Based on early beta tester feedback. Actual times vary depending on API complexity and user experience. Not a guarantee of performance.

1. 1

   Open the Jettson Visual Builder

   Navigate to jettson.ai/studio/builder. The canvas loads instantly — no setup, no dependencies, no CLI.

   jettson.ai/studio/builder

   Build MCP Server

   Define tools visually, generate server code automatically.

   + Add ToolSave Server

   Server Configuration

   Server Name*

   my-mcp-server

   Version

   1.0.0

   Description

   A brief description of your server

   No tools defined yet

   Add your first tool →

   </>Generated Code

   CopyDownload

   server.ts

   import { Server } from "@modelcontextprotocol/sdk";
   import { StdioServerTransport } from
     "@modelcontextprotocol/sdk/server";
   
   const server = new Server({
     name: "my-mcp-server",
     version: "1.0.0"
   });

2. 2

   Create a new server

   Click "New Server" and give it a name. Jettson scaffolds the MCP boilerplate — Server import, transport config, and entry point — automatically.

   jettson.ai/studio/builder

   New Server

   Server Name*

   weather-api

   Version

   1.0.0

   Description

   Weather forecast and alerts for any location

   CancelCreate Server
3. 3

   Add tool nodes

   Drag tool nodes onto the canvas. Each node becomes a callable tool in your MCP server. Name it, describe it, and define its purpose.

   jettson.ai/studio/builder

   Tools

   + Add Tool

   get_forecast

   Get weather forecast for a location

   location: stringdays: number

   get_alerts

   Get active weather alerts for a region

   state: string
4. 4

   Define parameters with Zod schemas

   For each tool, add parameters using the visual form. Jettson generates Zod validation automatically — strings, numbers, enums, arrays, optional fields.

   jettson.ai/studio/builder

   Parameters — get_forecast

   location

   z.string()

   City name or coordinates

   required

   days

   z.number()

   Number of forecast days

   optional

   units

   z.enum(["metric", "imperial"])

   Temperature units

   optional

   + Add Parameter
5. 5

   Connect to your API

   Configure the API endpoint, HTTP method, headers, and auth. Jettson wires the request into your tool handler and maps the response.

   jettson.ai/studio/builder

   API Connection — get_forecast

   Method

   GET

   Endpoint URL

   https://api.weather.gov/points/{location}

   Headers

   User-Agent:"jettson-weather/1.0"

   Authentication

   NoneAPI KeyBearer TokenOAuth 2.0
6. 6

   Preview generated TypeScript

   Watch clean, production-ready TypeScript generate in real time as you build. The code follows the official MCP SDK spec — no post-editing needed.

   jettson.ai/studio/builder

   </>Generated Code

   Live Preview

   weather-server.ts

   import { Server } from "@modelcontextprotocol/sdk";
   import { z } from "zod";
   
   const server = new Server({
     name: "weather-api",
     version: "1.0.0"
   });
   
   server.tool("get_forecast", {
     location: z.string(),
     days: z.number().default(5),
   }, async ({ location, days }) => {
     // Auto-generated by Jettson
     const res = await fetch(
       `https://api.weather.gov/points/${location}`
     );
     return res.json();
   });
   
   server.start();

7. 7

   Export or deploy

   Copy to clipboard, download as a .ts file, or deploy directly to Jettson Cloud Hosting for an always-on server with health monitoring.

   Copy to Clipboard

   Paste into your project

   Download .ts File

   Save and deploy anywhere

   Deploy to Cloud

   One-click · $19/mo

8. 8

   Connect to Claude, Cursor, or any MCP client

   Add your server to Claude Desktop, Cursor, VS Code, or any MCP-compatible agent. One config entry and your tools are live.

   claude_desktop_config.json

   {
     "mcpServers": {
       "weather-api": {
         "command": "npx",
         "args": ["weather-api"]
       }
     }
   }

   Claude DesktopCursorVS Code + CopilotLangChainCustom Agent