MCP explained: the protocol connecting AI to everything

If you've been following the AI tools space, you've probably seen 'MCP' mentioned everywhere. Model Context Protocol is an open standard that defines how AI applications communicate with external tools and data sources. Think of it as USB-C for AI - one protocol, infinite possibilities.

The problem MCP solves

Before MCP, every AI app had to build custom integrations for every service. Want your AI to read GitHub? Build a GitHub integration. Want Slack? Build a Slack integration. This doesn't scale. MCP provides a single interface that any tool can implement and any AI client can consume.

How it works

• MCP servers expose tools, resources, and prompts through a standard protocol.
• MCP clients (like Gotchi) connect to servers and auto-discover what's available.
• When a model needs to use a tool, it emits a tool call. The client routes it to the right server.
• Servers run locally alongside your AI - data flows between processes, never through external networks.

Using MCP in Gotchi

Gotchi is an MCP client out of the box. Add a server URL, and Gotchi auto-discovers all available tools. You can use them in conversations, wire them into agent workflows, or expose them via the command palette. No configuration needed beyond the URL.