What is MCP (Model Context Protocol)?
MCP is an open protocol that gives AI models a standard way to call external tools and data sources — one connector format instead of custom glue code per integration.
Definition
The Model Context Protocol (MCP) is an open standard, introduced by Anthropic in late 2024, that defines how AI applications connect to external tools and data. An MCP server exposes a set of typed capabilities — tools the model can invoke, resources it can read, prompt templates it can use — over a standard transport (stdio for local servers, Streamable HTTP for remote ones). Any MCP-capable client — a desktop assistant, an IDE, a voice agent — can attach any MCP server and immediately use its tools, no bespoke integration code per pairing.
The protocol matters because it collapses the N×M integration problem: before MCP, every AI app wrote custom glue for every API it touched; with MCP, a service publishes one server and every client gets it. In telecom terms: a phone-intelligence platform can expose HLR lookup, number rating, and antifraud checks as MCP tools, and any agent — including a live voice agent mid-call — can invoke them as naturally as a human analyst would open a dashboard. Authentication is typically bearer-token based for remote servers, and the client controls which tools the model may call.
Why it matters
MCP is the difference between an AI agent that talks about your data and one that acts on it. For anything agentic — support bots, voice agents, analyst copilots — exposing your product as an MCP server is rapidly becoming as expected as having a REST API was in 2015.
See it in action
MCP-powered tools in the SMS-24 AI agent →