Learn how to use Model Context Protocol (MCP) services on the Sealos platform to connect AI models with external tools and data sources through standardized interfaces.
The Model Context Protocol (MCP) is a game-changing standard that lets AI models talk to external tools and data sources seamlessly. Instead of building custom integrations for every service, developers can integrate once and connect to any MCP-compatible system.
Here's the challenge: AI models are smart, but they're isolated. They can't access your databases, check your billing, or run code in your development environment. To make AI truly useful, you need to connect it to real-world systems.
The traditional approach? Build custom integrations for every single service. Each one has different APIs, authentication methods, and data formats. It's a maintenance nightmare that gets worse as you add more tools.
MCP is like having a universal translator for AI integrations. Here's how it works:
For Developers: Write one MCP integration and connect to any MCP-compatible service. No more custom connectors for every tool.
For Service Providers: Build one MCP interface and instantly work with any MCP-enabled AI application.
Think USB-C for AI: Just like USB-C replaced dozens of different charging cables, MCP replaces dozens of different API integrations with one standard protocol.
MCP uses a simple client-server model with three key components:
MCP Host: Your AI application (like Cursor, VS Code, or ChatGPT)
MCP Client: The connection bridge that your AI app creates
MCP Server: The external service that provides tools and data (like Sealos)
Simple Example: Your Cursor editor (Host) creates a connection (Client) to talk to Sealos services (Server). Want to connect to multiple services? Your editor just opens multiple connections.
Sealos has built MCP servers for all its major platform capabilities. Using StreamableHttp communication, these servers work seamlessly with any MCP-compatible IDE or AI application.
Bottom line: You can now control your entire Sealos infrastructure through natural language conversations with AI.
Cline is a powerful AI coding assistant that runs directly in VS Code with native MCP support. It can write code, execute commands, browse the web, and more.
Setup Steps:
Install the Cline extension in VS Code and restart