If you've used Claude, Cursor, or Windsurf recently, you've probably seen "MCP" mentioned. But most explanations are either too abstract or too deep in the spec.
Here's the practical version.
What Is MCP?
Model Context Protocol is a standard that lets AI assistants use external tools. Think of it as USB for AI:
Before MCP: AI → custom integration → Tool A
AI → different integration → Tool B
AI → yet another → Tool C
With MCP: AI → MCP → Any Tool
One protocol, infinite tools.
Why Should You Care?
If you build tools, APIs, or services — MCP lets AI assistants use them directly. Your users can say "search my database" or "create a ticket" and the AI handles it.
If you use AI assistants — MCP gives them superpowers. Instead of copy-pasting between tools, the AI does it for you.
A Simple MCP Server in Python
from mcp.server import Server
from mcp.types import Tool, TextContent
import requests
server = Server("weather-server")
@server.tool()
async def get_weather(city: str) -> list[TextContent]:
"""Get current weather for any city."""
# Using Open-Meteo (free, no API key)
geo = requests.get(
"https://geocoding-api.open-meteo.com/v1/search",
params={"name": city, "count": 1}
).json()
if not geo.get("results"):
return [TextContent(type="text", text=f"City '{city}' not found")]
lat = geo["results"][0]["latitude"]
lon = geo["results"][0]["longitude"]
weather = requests.get(
"https://api.open-meteo.com/v1/forecast",
params={"latitude": lat, "longitude": lon, "current_weather": "true"}
).json()["current_weather"]
return [TextContent(
type="text",
text=f"{city}: {weather['temperature']}C, wind {weather['windspeed']} km/h"
)]
@server.tool()
async def get_crypto_price(coin: str) -> list[TextContent]:
"""Get current cryptocurrency price."""
data = requests.get(
"https://api.coingecko.com/api/v3/simple/price",
params={"ids": coin.lower(), "vs_currencies": "usd"}
).json()
price = data.get(coin.lower(), {}).get("usd", "not found")
return [TextContent(type="text", text=f"{coin}: ${price}")]
if __name__ == "__main__":
server.run()
How to Use It
Add to your Claude Desktop config (claude_desktop_config.json):
{
"mcpServers": {
"weather": {
"command": "python",
"args": ["weather_server.py"]
}
}
}
Now Claude can check weather and crypto prices directly.
Real MCP Servers You Can Use Today
| Server | What It Does |
|---|---|
| GitHub MCP | Manage repos, issues, PRs |
| Filesystem | Read/write local files |
| PostgreSQL | Query databases |
| Notion | Manage pages and databases |
| Slack | Send and read messages |
| Brave Search | Web search |
| Playwright | Browser automation |
Full list: awesome-mcp-servers
Building MCP Servers for Business
The real power is custom MCP servers for specific use cases:
- Market Research MCP — feed AI with competitor data, pricing, market trends
- Lead Finder MCP — let AI discover and qualify leads from public data
- SEO Analyzer MCP — AI audits websites and suggests improvements
- Social Monitor MCP — AI tracks brand mentions across platforms
I've built several of these on Apify.
The MCP Ecosystem Is Growing Fast
Every major AI tool is adding MCP support:
- Claude Desktop and Claude Code (Anthropic)
- Cursor (AI code editor)
- Windsurf (AI IDE)
- Continue.dev (open source)
If you build developer tools, adding MCP support is becoming table stakes.
Are you building or using MCP servers? What tools have you connected?
Resources: MCP Spec | My MCP Servers | MCP Cookbook
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