Getting Started with MCP Servers: A Practical Guide

The Model Context Protocol (MCP) is an open standard created by Anthropic that lets AI assistants connect to external tools and data sources. Think of it as a USB-C port for AI — a single protocol that works across different AI clients and servers.

What Is MCP?

MCP defines how an AI client (like Claude Code, Cursor, or VS Code with an AI extension) communicates with external servers that provide tools, resources, and prompts. Instead of each AI tool building custom integrations, MCP provides a universal interface.

An MCP server exposes three types of capabilities:

Tools: Functions the AI can call (e.g., "search_files", "create_issue", "run_query")

Resources: Data the AI can read (e.g., file contents, database schemas, API docs)

Prompts: Reusable prompt templates for common tasks

Setting Up Your First MCP Server

Prerequisites

You need an MCP-compatible client. The most common options are:

Claude Code (terminal) — built-in MCP support

Cursor (IDE) — configure in settings

VS Code — via extensions like Continue

Installing the Filesystem Server

The filesystem server is the simplest to start with. It gives your AI assistant read/write access to specified directories.

For Claude Code, add to your config:
claude mcp add filesystem -s user -- npx -y @modelcontextprotocol/server-filesystem /path/to/your/project

Installing the GitHub Server

The GitHub MCP server lets your AI create issues, review PRs, and search code:

Set your GitHub token
export GITHUB_PERSONAL_ACCESS_TOKEN=ghp_your_token_here

Add to Claude Code
claude mcp add github -s user -- npx -y @modelcontextprotocol/server-github

Transport Types

MCP servers communicate via two transport mechanisms:

stdio — The server runs as a local process and communicates via stdin/stdout. Most common for local tools.

HTTP (SSE) — The server runs as a web service. Used for remote/shared servers.

Security Considerations

Always review what permissions an MCP server requests before installing

Use read-only modes when available for database servers

Scope filesystem access to specific directories

Rotate API tokens regularly for third-party service servers

Next Steps

Once you are comfortable with basic servers, explore database servers (PostgreSQL, SQLite), communication servers (Slack, Discord), and cloud servers (AWS, Vercel) to build a powerful AI-assisted development workflow.