MCP Integration Quickstart.

Model Context Protocol (MCP) is an open standard that lets AI agents connect to external tools through a single, universal interface. Instead of building a custom integration for every tool your agent needs to access, you set up an MCP server for each tool and every agent connects through the same protocol.

Think of it as USB-C for AI. One cable, any device. One protocol, any tool. MCP was created by Anthropic in late 2024 and has since been adopted by OpenAI, Google, Microsoft, and hundreds of open-source projects.

The fastest way to get started is with a community-maintained MCP server. The MCP ecosystem has pre-built servers for most popular tools.

# Python
pip install mcp

# Node.js
npm install @modelcontextprotocol/sdk

from mcp.server import Server
from mcp.types import Tool, TextContent

server = Server("my-tool-server")

@server.tool()
async def lookup_contact(name: str) -> list[TextContent]:
    """Look up a contact in the CRM by name."""
    # Your CRM lookup logic here
    result = crm_client.search(name)
    return [TextContent(
        type="text",
        text=f"Found: {result.name}, {result.email}"
    )]

# The agent discovers this tool automatically
# and can call it through the MCP protocol

The key insight: you define what the tool does (the function signature and description), and MCP handles how the agent discovers and calls it. The agent never needs to know the internal implementation details.