What is MCP?
The Model Context Protocol (MCP) is an open standard for connecting AI clients — chat agents, IDEs, and CLIs — to external tools and data through one consistent contract. Instead of hand-wiring a bespoke integration for every model and every app, you expose your capabilities once as an MCP server and any compatible client can discover and call them.Why MCP matters
- One contract, many clients. A single server works across Claude, Cursor, VS Code, Codex, and more without rewriting business logic.
- Clear separation of concerns. Client UX stays independent from backend tool implementation.
- Predictable tool discovery. Agents introspect the available tools, their inputs, and their descriptions at runtime.
Core building blocks
Client
The AI app or editor that discovers and calls tools (Cursor, Claude Code, ChatGPT, and others).
Server
The MCP endpoint that exposes tools, resources, and prompts to clients.
Transport
How requests flow: Streamable HTTP, SSE, or stdio for local development.
Auth boundary
The token and permission model controlling who can reach the server.
Tools, resources, and prompts
An MCP server can expose three kinds of primitives:- Tools — callable functions the agent invokes (for example,
confirm_payment_intent). Each tool has a typed input schema and a description the agent reads to decide when to call it. - Resources — readable data the agent can pull into context (files, records, documents).
- Prompts — reusable prompt templates the server offers to clients.
Tool descriptions are not cosmetic — they are how an agent decides which tool to call. Vague descriptions lead to wrong or skipped calls. This is exactly why MCPCloud rewrites every tool description for agent comprehension during the build pipeline.
The description problem
A raw API spec describes endpoints for humans. Agents need richer, behavior-oriented descriptions. Compare:
The second version gives the agent enough context to use the tool correctly and safely.