Model Context Protocol Explained: Host, Server & Client Roles in AI-Native Workflows

What is the Model Context Protocol?

The Model Context Protocol (MCP) is an open specification that lets AI applications safely pull live data from external tools without exposing credentials or writing custom glue code. Think of it as a USB-C port for large language models: one universal socket that turns any data source into a plug-and-play extension of the model’s short-term memory.

Why MCP Matters Today

Traditional integrations require brittle API wrappers, frequent re-authentication and duplicated logic across every new model provider. MCP replaces that chaos with three concise primitives—host, server and client—that separate concerns, enforce least-privilege access and keep sensitive tokens inside your infrastructure boundary.

The Three Actors in MCP

Host – the long-running process that owns the user session (e.g., Claude Desktop, an IDE plugin or a Slack bot). It manages configuration files, spawns servers on demand and routes requests.
Server – a lightweight adapter that translates MCP calls into native API calls of a single tool (Postgres, Jira, Stripe, etc.). It exposes a JSON-RPC interface and never stores credentials; instead it receives short-lived tokens injected by the host.
Client – the SDK inside the LLM application that speaks the MCP wire protocol. It discovers available servers, renders tool descriptions to the model as natural language and marshals arguments back to the server.

Lifecycle of a Single Query

When a user asks “Which customers churned last month?”, the client inside Claude converts the question into an MCP tools/list call. The host forwards it to the Postgres server, which returns a schema. The model then fills the required parameters; the host injects the read-only DB token, the server executes SQL and streams rows back. The model reasons over the live result and answers in plain English—all within seconds and without ever persisting the database password.

Security & Governance Benefits

Credentials stay inside the host’s keychain; servers remain stateless.
Fine-grained scopes (read, write, admin) are declared in the server manifest and enforced by the host.
Audit logs capture every MCP call, making compliance trivial.

Getting Started

Install the @modelcontextprotocol/sdk, create a claude_desktop_config.json file pointing to your server executable and launch Claude. Within minutes your model can query internal APIs as naturally as it quotes Wikipedia.

MCP turns isolated LLMs into extensible, enterprise-grade co-workers—no custom Python scripts required.