Definition
The Model Context Protocol (MCP) is an open standard, introduced by Anthropic in late 2024, for connecting AI applications to external tools, data sources, and workflows. Its purpose is to replace the tangle of one-off, custom integrations with a single uniform interface, often described as "a USB-C port for AI applications." Build a connector once as an MCP server, and any MCP-compatible client, Claude, ChatGPT, and many code editors, can use it without bespoke glue code.
How it works
MCP follows a client-server architecture. The AI application (the host) runs an MCP client; each external capability is exposed by an MCP server. A server can offer three things: tools (functions the model can call, like a database query), resources (data the model can read, like files or logs), and prompts (reusable templated workflows). Servers run locally over standard input/output or remotely over HTTP, so a server can sit on the same machine as the model or across a network.
Why it matters for sovereignty
For self-hosting operators, MCP is significant because it lets a local AI agent reach your own infrastructure, a Bitcoin node, a miner's API, a monitoring database, through servers you write and control, with nothing routed through a vendor cloud. The protocol is the connective tissue that turns an isolated model into a system that can act on your real environment.
The same exposure also widens the attack surface: any data an MCP server returns is untrusted input, so MCP-enabled agents must be hardened against prompt injection and given least-privilege credentials.
In Simple Terms
The Model Context Protocol (MCP) is an open standard, introduced by Anthropic in late 2024, for connecting AI applications to external tools, data sources, and…