What is an MCP server?

MCP, in one sentence

The Model Context Protocol (MCP) is an open standard for connecting AI assistants to external tools and data. Instead of baking every integration into the model, MCP defines a common language so any compatible assistant can discover and call any compatible tool — the way a USB port lets any device talk to any computer.

What an MCP server actually does

An MCP server is a program that exposes a set of tools — each with a name, a description, and a typed input schema. The AI client (Claude Desktop, an IDE, an agent framework) connects to the server, reads the list of tools, and can then call them with structured arguments and get structured results back. Servers run over stdio for local desktop clients or over HTTP for remote deployments.

The flow is simple:

• The server advertises its tools (name, purpose, parameters).
• The model decides a tool is needed and calls it with arguments.
• The server runs the work and returns a result the model can read.

Why search & knowledge are ideal MCP tools

Language models are confident but ungrounded — they’ll fill a gap with a plausible guess. A retrieval tool over MCP gives the model a way to look something up instead of inventing it. That makes search, fetch, and citation among the most useful MCP tools an agent can have.

ColdState’s MCP server

ColdState ships an MCP server over a 48.4M-entry knowledge base: search and browse tools, plus a set of agent-native primitives — fetch, cite, verify, snapshot — built so an AI can ground, cite, and reproduce its answers. Because retrieval is deterministic, the same tool call returns the same result every time, which is exactly what reproducible agents need.