What is MCP? Understanding the Model Context Protocol

Maybe you have already heard the term MCP, but do you really know what it is?

What is MCP?

MCP (Model Context Protocol) is an open protocol created by Anthropic that standardizes how AI models communicate with external systems. Think of it as a universal adapter that allows AI assistants like Claude Code to interact with databases, APIs, file systems, and other tools in a secure and consistent way.

Before MCP, every AI integration required custom code and specific implementations. MCP solves this problem by providing a common language that any AI can use to access any compatible tool.

Why Does MCP Matter?

1. Standardization: One protocol to connect AI with any tool or data source (Jira, Figma, Github, etc...).

2. Security: Built-in permission systems and sandboxed execution.

3. Flexibility: Add new capabilities to AI assistants without changing the model itself.

4. Interoperability: Tools built for one AI can work with any MCP-compatible assistant.

How Does MCP Work?

MCP follows a client-server architecture:

1. MCP Host: The AI application (like Claude Desktop or an IDE extension) that wants to access external capabilities.

2. MCP Client: Maintains connections between the host and servers.

3. MCP Server: Provides specific capabilities like file access, database queries, or API calls.

When you ask an AI assistant to perform a task that requires external data, the MCP client routes that request to the appropriate server, which executes the action and returns the result.

Core Concepts

MCP servers can expose three types of capabilities:

Tools: Functions the AI can call to perform actions.

{
  "name": "read_file",
  "description": "Read contents of a file",
  "parameters": {
    "path": { "type": "string" }
  }
}

Resources: Data sources the AI can access (files, database records, API responses).

Prompts: Pre-defined templates that help the AI understand how to use the server's capabilities.

Where to Find MCP Servers

You can find MCP servers at Smithery, a repository with hundreds of ready-to-use servers.

Some popular ones:

• GitHub: Manage repositories, issues, and pull requests
• Slack: Send messages and interact with channels
• PostgreSQL/MySQL: Query databases directly
• Filesystem: Read and write files on your machine
• Context7: Access up-to-date documentation

Which Tools Support MCP?

MCP is supported by several AI tools:

• Claude Desktop
• Claude Code (CLI)
• Cursor
• Windsurf
• And many others...

An Example

Let me show you MCP in action using Context7 (an MCP server that gives your AI access to up-to-date documentation) and Claude Code.

Installing an MCP Server

claude mcp add --transport http context7 https://mcp.context7.com/mcp

That's it. One command and Claude Code now has access to documentation from hundreds of libraries.

Using It

Just mention it in your prompt:

create an API that returns Game of Thrones characters' names and descriptions using Node.js and Express.js, use Context7 MCP

Claude will fetch the latest Express.js docs and generate code following current best practices. No outdated patterns, no deprecated methods.

This is the power of MCP: adding new capabilities to your AI with a single command.

Conclusion

MCP is more than just a protocol—it's a new paradigm for AI development. By standardizing how AI models interact with the world, it makes AI assistants more capable, secure, and extensible.

Whether you're a developer looking to extend AI capabilities or a user wanting to get more from your AI tools, understanding MCP is becoming essential knowledge in the AI landscape.

Want to learn more? Check the official Model Context Protocol documentation.