MCP ProtocolMCP Protocol

By 2024, the most useful thing an AI assistant could do was reach beyond its training data: query a database, read a codebase, search a wiki, file a ticket. But every connection was a bespoke integration. With M applications and N tools, the ecosystem faced an M-times-N wall of custom connectors, each solving the same problem slightly differently.

In November 2024, Anthropic released the Model Context Protocol, an open standard for wiring AI applications to external tools and data. The pitch was deliberately mundane, a USB-C port for AI: build one MCP server for your tool, and any MCP-compatible assistant can use it. M-times-N becomes M-plus-N.

The design is a client-server architecture speaking JSON-RPC. Servers expose three primitives: tools the model can invoke, resources it can read, and prompts that package common workflows. The application hosts a client, the model decides when to call what, and the protocol handles discovery and transport.

Adoption was unusually fast for infrastructure. Early on, developers published thousands of community servers for everything from GitHub to Postgres to Slack, and in 2025 OpenAI and Google DeepMind, Anthropic's chief rivals, announced support, effectively ending the standards contest before it started.

MCP arrived just as the industry pivoted from chatbots to agents, and the timing was not a coincidence. Agents are only as capable as the tools they can reach, and a shared protocol turned tool access from a per-vendor engineering project into an ecosystem. It also concentrated new security questions, around prompt injection and tool permissions, that enterprises are still working through.