What is MCP?
The Model Context Protocol (MCP) is an open standard designed to standardize how AI models interact with external data and tools. It solves the "many-to-many" problem where every AI assistant needs a custom integration for every data source. With MCP, you build a connector (Server) once, and it works with any MCP-compliant application (Client).
Core Components
- MCP Client: The AI application (e.g., Claude Desktop, Zed IDE, Gemini CLI) that consumes context and uses tools.
- MCP Host: The runtime environment that manages the connection between clients and servers.
- MCP Server: A lightweight service that exposes resources (data), tools (functions), and prompts to the client.
Enabling External Tools
MCP allows servers to define Tools—executable units of logic that the model can invoke. Instead of hard-coding API calls into the LLM application, the Server advertises its tools (e.g., read_file, query_database). The Client (LLM) decides when to call these tools based on user intent, enabling dynamic and safe interaction with the outside world.
The Ecosystem
The MCP ecosystem is rapidly growing, with servers available for:
- Filesystems: Securely reading/writing local files.
- Databases: PostgreSQL, SQLite providers.
- SaaS: GitHub, Slack, Google Drive integrations.
- Developer Tools: Git, Sentry, browser automation.