Understanding MCP Servers

MCP servers are programs that expose specific capabilities to AI applications through standardized protocol interfaces.

Core Server Features

Servers provide functionality through three building blocks:

Feature	Explanation	Who controls it
Tools	Functions that the LLM can actively call. Used to perform actions.	Model
Resources	Passive data sources for read-only access to context info.	Application
Prompts	Pre-built instruction templates for users (e.g. slash commands).	User

Tools

Tools enable AI models to perform actions. Each tool defines a specific operation with typed inputs (JSON Schema) and outputs.

• list: Discover available tools.
• call: Execute a specific tool.

Example definition:

{
  "name": "searchFlights",
  "description": "Search for available flights",
  "inputSchema": { ... }
}

Resources

Resources provide structured access to information (files, databases, APIs) as context.

• Direct Resources: Fixed URIs (e.g., file:///path/doc.md).
• Resource Templates: Dynamic URIs (e.g., travel://activities/{city}).
• Operations: list, read, subscribe.

Prompts

Prompts are user-controlled templates (like "Plan a vacation"). They help structure interactions.

• list: Discover prompts.
• get: Retrieve prompt details and arguments.

Bringing Servers Together

The power of MCP emerges when multiple servers work together. For example, a Travel Server, Weather Server, and Calendar Server can be combined by the Host to fulfill a complex user request like "Plan my vacation".