MCP Introduction
Model Context Protocol (MCP) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications - it provides a standardized way to connect AI models to different data sources and tools.
Why MCP?
MCP helps you build agents and complex workflows on top of LLMs. Large Language Models frequently need to integrate with data and tools, and MCP provides:
- A growing list of pre-built integrations that your LLM can directly plug into
- The flexibility to switch between LLM providers and vendors
- Best practices for securing your data within your infrastructure
General Architecture
At its core, MCP follows a client-server architecture where a host application can connect to multiple servers:
- MCP Hosts: Programs like Claude Desktop, IDEs, or AI tools that want to access data through MCP
- MCP Clients: Protocol clients that maintain 1:1 connections with servers
- MCP Servers: Lightweight programs that each expose specific capabilities through the standardized Model Context Protocol
- Local Data Sources: Your computer's files, databases, and services that MCP servers can securely access
- Remote Services: External systems available over the internet (e.g., through APIs) that MCP servers can connect to
Key Features
Resources
Context and data for the user or the AI model to use
Prompts
Templated messages and workflows for users
Tools
Functions for the AI model to execute
Sampling
Server-initiated agentic behaviors and recursive LLM interactions
For more information, visit the official MCP website.