How to Deploy Remote MCP Servers in Python (Step-by-Step Guide for Custom Self-Hosted MCP Servers)

Want to build your own custom AI backend tool that integrates seamlessly with Claude, Cursor, or Windsurf?
This guide walks you through deploying a Remote MCP server using Python and FastMCP, hosted effortlessly on a Hallo-Webseite.de VPS— the fastest way to launch your own tools like SEO analyzers, SSL checkers, or data pipelines.

What is a Remote MCP Server?

A Remote MCP server is a lightweight backend that responds to structured prompts from AI interfaces like Claude, Cursor, or Windsurf using the Model Context Protocol (MCP).
By using FastMCP, you can create and deploy Python-based tools with:

# AI-assisted inputs

# Structured JSON outputs

# Simple, portable hosting

✅ Why Use FastMCP with Hallo-Webseite.de?

⚙️No frontend or UI required

# Write tools in pure Python

# Deploy via Docker in minutes

# Works instantly with Claude, Cursor, and Windsurf

# 1-click deploy on Hallo-Webseite.de VPS

To help you get started, we created sample SEO Checker MCP template this MCP template can be used as a starting point for building your own remote tools, whether it’s an SEO analyzer, SSL checker, uptime monitor, or any custom Python-powered backend for AI clients.

Step 1: Install Ubuntu 24 with MCP Server template

Navigate to your Hallo-Webseite.de VPS OS section and install MCP Server template.

Hallo-Webseite.de will:
Pull the repo and build the image

Open port8080

Give you a live URL like:

http://your-seo-app.hstgr.cloud/mcp

Step 2: Add the Server to Cursor (or other MCP client)

For Cursor

Go to Settings > Tools & Integrations > MCP Tools

Click Add New Tool

Fill with your VPS hostname and Restart Cursor:

{
  "mcpServers": {
    "seo-checker": {
      "url": "http://your-seo-app.hstgr.cloud:8080/mcp",
      "description": "Professional SEO analysis and optimization recommendations"
    }
  }
}

Step 3: Test Your MCP Server Inside Cursor

Once you’ve added your server to Cursor, it’s time to test it by prompting the tool.
Try one of these sample prompts in any Cursor chat:
"Analyze the SEO of example.com"

"Do a quick SEO check on github.com"

"Check the meta tags for blog.mywebsite.com"

"Compare SEO of google.com, bing.com, and duckduckgo.com"

If everything is working, you’ll see a detailed, structured response from your remote server — powered by your own Python code.
How to Deploy Remote MCP Servers in Python (Step-by-Step Guide for Custom Self-Hosted MCP Servers)

✅ Customize the Tool – Build Your Own

Inside the repo, open remote-seo-checker.py:

from fastmcp import Tool, run

@Tool
def custom_hello_world(name: str) -> str:
    return f"Hello, {name}. This is your custom MCP tool!"

run()

To build your own:

Add new functions

Decorate them with @Tool

Restart the container

FastMCP will auto-generate the API schema — no manual routing required.

✅ Alternative: Create New Tools with AI

You can create your own MCP even faster using AI:
Upload remote-seo-checker.py to ChatGPT or Claude and ask: “Create a new MCP tool using this format for example, an SSL certificate checker.”
You’ll get working code you can plug in and deploy immediately.

Build tools like:
# SSL Checkers

# Uptime Monitors

# Analytics Dashboards

# PDF Metadata Extractors

# Sitemap Auditors

If you can write a ChatGPT prompt, you can launch a production-ready AI backend.

✅ Optional: Run Locally for Development

Clone the repo

Set up virtual env:

python -m venv venv source venv/bin/activate

Install dependencies:

pip install -r requirements.txt

Start the server:

python remote-seo-checker.py

Access athttp://localhost:8080/mcp

✅ Final Thoughts

With FastMCP + Hallo-Webseite.de VPS, you can deploy custom MCP tools in minutes:
# Just write Python

# Deploy with Docker

# Integrate with AI clients instantly

# Fully extensible — from SEO to SSL to analytics