Boost Your Agents with MCPs - Launch First Real-world Agentic App

Why MCP? MCP stands for Model Context Protocol. Think of it as a standardised USB-C port for AI tools. Instead of every AI application inventing its own plugin system, MCP defines a common interface: a server exposes tools, a client (our agent here) discovers and calls them. The beauty is that the same MCP server can be reused by Claude Desktop, by a Strands agent, by any MCP-compatible client — without changing a single line of server code. This is the interoperability that the ecosystem has been missing. Here, we use FastMCP, a Python library that reduces an MCP server to almost nothing: from mcp.server import FastMCP mcp = FastMCP("Calculator Server") @mcp.tool(description="Add two numbers together") def add(x: float, y: float) -> float: return x + y if __name__ == "__main__": mcp.run(transport="stdio") That is a fully functional MCP server. The decorator @mcp.tool is all you need to expose a function to any MCP client. Review: Our Analyst (Sub-agent) We start with creating our f