MCP Servers Explained: What Developers Need to Know

The Model Context Protocol is how AI agents connect to external tools. Learn what MCP servers are, how they work, and why they matter for your workflow.

If you use Claude Code, Cursor, or any modern AI coding agent, you've probably heard of MCP — the Model Context Protocol. But what exactly is it, and why should you care?

MCP in one sentence

MCP is an open protocol that lets AI agents call external tools in a standardized way — like USB for AI integrations.

The problem MCP solves

Before MCP, every AI tool integration was custom. Want to connect Claude to a database? Write a custom wrapper. Want to add file search? Another custom integration. Each AI agent had its own integration format, and none were compatible with each other.

MCP standardizes this. A tool built for MCP works with any MCP-compatible agent — Claude Code, Cursor, Windsurf, and more. Build once, work everywhere.

How MCP works

An MCP setup has three parts:

MCP Client — The AI agent (e.g., Claude Code). It discovers and calls tools.
MCP Server — A process that exposes tools. It runs locally or connects to a remote service.
Transport — Communication between client and server, typically via stdio (standard input/output).

When you add an MCP server to your .mcp.json, the AI agent starts the server process and discovers what tools are available. The agent can then call these tools during your conversation.

What an MCP server exposes

An MCP server can expose:

Tools — Functions the agent can call (e.g., memory_store, search_files)
Resources — Data the agent can read (e.g., documentation, configuration)
Prompts — Pre-built prompt templates

Example: Agent-Memo MCP server

Agent-Memo.AI's MCP server exposes 14 tools for memory management. When you configure it in .mcp.json, your AI agent gets access to:

memory_store — Save a memory to the cloud
memory_recall — Semantic search across memories
kg_add — Add entity relationships
kg_query — Query the knowledge graph
...and 10 more tools

The configuration is a single JSON file — no SDK, no wrapper code, no boilerplate:

{
  "mcpServers": {
    "agent-memo": {
      "command": "npx",
      "args": ["-y", "@agent-memo/mcp-client"],
      "env": {
        "AGENTMEMO_TOKEN": "your-token"
      }
    }
  }
}

Building your own MCP server

MCP servers can be built in any language. The most common approach is TypeScript with the official @modelcontextprotocol/sdk package. A minimal server that exposes one tool is about 50 lines of code.

The MCP ecosystem

The MCP ecosystem is growing rapidly. There are MCP servers for databases, file search, web scraping, CI/CD, issue tracking, and more. As more agents adopt MCP, tools built for the protocol become instantly available to a wider audience.

For developers, MCP means you can extend your AI agent's capabilities without waiting for the agent vendor to add features. If you need a tool that doesn't exist, you can build an MCP server for it.

Learn more about Agent-Memo's MCP integration