MCP ExplorerExplorer

Spawn Mcp

@cameronking4on 5 months ago
1 MIT
FreeCommunity
AI Systems
#mcp-server#remote-mcp-server#stdio-wrapper#hosted-mcp-servers#supermachine
Open source supermachine proof of concept. Self host a MCP server with STDIO transport and get instant SSE Url

Overview

What is Spawn Mcp

spawn-mcp is an open-source proof-of-concept server designed for the Model Context Protocol (MCP) that enables instant Server-Sent Events (SSE) streaming using STDIO transport.

Use cases

Use cases include developing real-time applications, streaming model responses for AI applications, and creating interactive web services that require immediate data updates.

How to use

To use spawn-mcp, clone the repository, install dependencies, set up a PostgreSQL database, configure environment variables, and run the development server. For deployment, push your code to GitHub/GitLab and create a web service on Render.

Key features

Key features include a simple UI for managing MCP server configurations, stable SSE endpoint generation for each configuration, real-time model response streaming via SSE, and easy deployment with one-click on Render.

Where to use

spawn-mcp can be used in various fields such as web development, real-time data streaming applications, and any project requiring instant server-client communication.

Content

MCP SSE Server POC

A proof-of-concept server for STDIO transport of Model Context Protocol (MCP) into instant Server-Sent Events (SSE) streaming, deployable as a service. Instant remote hosted MCP servers with zero infrastructure work.

Features

  • Create and manage MCP server configurations via a simple UI
  • Generate stable SSE endpoints for each configuration
  • Stream real-time model responses via SSE
  • Built with Express, Drizzle ORM, and PostgreSQL
  • One-click deployment on Render

Local Development

Prerequisites

  • Node.js (v18 or later)
  • PostgreSQL database

Setup

  1. Clone this repository:
git clone https://github.com/yourusername/mcp-sse-poc.git
cd mcp-sse-poc
  1. Install dependencies:
npm install
  1. Set up your local PostgreSQL database and create a .env file with your database connection string:
DATABASE_URL=postgresql://username:password@localhost:5432/mcp_sse_db
  1. Generate and run migrations:
npm run generate
npm run migrate
  1. Start the development server:
npm run dev
  1. Open your browser and navigate to http://localhost:3000

Deployment on Render

1. Push Your Code to GitHub/GitLab

Make sure your repository includes all the files in this project.

2. Create a Web Service on Render

  1. Log in to your Render Dashboard
  2. Click New → Web Service
  3. Connect your GitHub/GitLab repository
  4. Configure the service:
    • Name: Choose a name (e.g., mcp-sse-poc)
    • Environment: Node
    • Build Command: npm install (this will trigger the postinstall script that builds and migrates)
    • Start Command: npm start
  5. Click Create Web Service

3. Add a PostgreSQL Database

  1. In Render, click New → PostgreSQL Database
  2. Name it (e.g., mcp-sse-db)
  3. Select the free plan
  4. Click Create Database
  5. Copy the provided DATABASE_URL connection string

4. Configure Environment Variables

  1. Go back to your Web Service
  2. Navigate to the Environment tab
  3. Add the following environment variable:
    • Key: DATABASE_URL
    • Value: Paste the connection string you copied

5. Deploy

Render will automatically deploy your application. Once deployed, you can access it at the URL provided by Render.

Usage

  1. Open your deployed application in a browser
  2. Create a new MCP server configuration by entering a name and JSON configuration
  3. Save the configuration to generate an SSE URL
  4. Use the SSE URL in your client application to stream model responses

Example Configuration

{
  "mcpServers": {
    "playwright": {
      "command": "npx",
      "args": [
        "@playwright/mcp@latest"
      ]
    }
  }
}

Model Context Protocol (MCP)

The Model Context Protocol is a lightweight, STDIO-based specification for interacting with language models over a standard input/output interface. It allows for real-time streaming of model responses and is designed to be simple and extensible.

Core Concepts

  1. STDIO Transport

    • Input: JSON blob describing context messages
    • Output: Incremental response tokens streamed to stdout
    • Errors & Events: Non-blocking notifications on stderr
  2. JSON Message Format

    {
      "context": [
        {
          "role": "system",
          "content": "You are a helpful assistant."
        },
        {
          "role": "user",
          "content": "Translate to French: Hello, world!"
        }
      ],
      "stream": true
    }
  3. Server-Sent Events (SSE)

    • Each JSON chunk becomes an SSE event
    • Perfect mapping to MCP’s unidirectional streaming model

License

MIT

Tools

No tools

Comments

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