The biggest limitation of AI assistants is that they can only work with what you paste into the chat. MCP (Model Context Protocol) changes this fundamentally. MCP is an open standard that lets you expose your own data and services as tools Claude can call. Instead of copy-pasting database results into the chat, Claude fetches them live from your MCP server. How it works: 1. You create an MCP server (a simple TypeScript/Python file) 2. You define tools with names, parameters, and handlers 3. You wire it via a .mcp.json config file 4. The agent auto-starts your server and can call your tools Example — a logistics MCP server with 3 tools: • track_shipment(trackingCode) — returns real-time status • list_shipments(status?) — filters by status • shipment_stats() — aggregate dashboard data The .mcp.json wiring: { "mcpServers": { "cargo-ops": { "command": "npx", "args": ["tsx", "mcp-server/index.ts"] } } } After saving this file, the agent automatically starts the MCP server and has access to all your tools. No manual steps. Why this matters for teams: MCP turns your internal APIs, databases, and services into first-class tools the AI can use. Your agent stops being a text generator and becomes a real operational assistant that queries your production data, triggers workflows, and reports back.