MCP (Model Context Protocol) — Everything You Need to Know

MCP (Model Context Protocol) is an open standard created by Anthropic that defines how AI models connect to external tools, data sources, and services. Think of it as a USB-C port for AI — a single, standardized interface that replaces the mess of custom integrations each tool vendor previously had to build. Before MCP, connecting an AI assistant to your database, your company's internal APIs, or a third-party service meant writing bespoke glue code for every combination of model and tool. MCP provides a universal protocol layer so that any MCP-compatible client (like Claude Code, Cursor, or Windsurf) can connect to any MCP server, and any MCP server can expose its capabilities to any compatible client.

Latest Developments

MCP adoption has accelerated significantly since Anthropic open-sourced the specification. Major IDE and AI tool vendors — including Cursor, Windsurf, Cline, and Zed — have added MCP client support, making servers written once usable across multiple development environments. The ecosystem of community-built MCP servers has grown rapidly, covering databases (PostgreSQL, SQLite), cloud providers (Amazon Web Services, Google Cloud), developer tools (GitHub, Linear, Sentry), and knowledge bases (Notion, Confluence).

Anthropic has continued iterating on the protocol itself, with recent updates improving authentication flows for remote MCP servers and introducing streamable HTTP transport alongside the original stdio-based communication. These changes make MCP viable for production deployments where servers run remotely rather than on a developer's local machine.

For detailed coverage on how MCP fits into the Claude Code extension ecosystem, see our deep dive on Claude Code's extension stack: Skills, Hooks, Agents, and MCP.

Key Features and Capabilities

Client-server architecture: MCP uses a straightforward client-server model. The AI application (client) discovers and calls tools exposed by MCP servers. Servers declare their capabilities — available tools, resources, and prompts — through a standardized discovery mechanism. This decoupling means server authors don't need to know which AI model will call their tools.

Three core primitives: MCP servers expose three types of capabilities:

Tools — executable functions the AI can invoke (e.g., query a database, create a GitHub issue, send a Slack message)
Resources — read-only data the AI can access (e.g., file contents, API documentation, configuration)
Prompts — reusable prompt templates that servers can offer to clients for common workflows

Transport flexibility: MCP supports multiple transport layers. Stdio runs the server as a local subprocess — simple, fast, and requires no network configuration. Streamable HTTP (and the earlier SSE-based transport) enables remote servers, suitable for shared team infrastructure or cloud-hosted integrations.

Security model: Clients control which servers are connected and users approve tool invocations. MCP servers run with explicit permissions, and the protocol supports OAuth-based authentication for remote servers accessing protected APIs.

Composability: Multiple MCP servers can run simultaneously. A single Claude Code session might connect to a GitHub server, a database server, and a monitoring server — each providing specialized tools that the agentic workflow orchestrates as needed. Our analysis of MCP vs CLI vs Skills breaks down when to use each extension mechanism.

Common Questions

What is MCP used for? MCP lets AI assistants interact with external systems — databases, APIs, cloud services — through a standardized protocol instead of custom integrations
Do I need to write my own MCP server? Not necessarily. The community maintains hundreds of pre-built servers for popular tools. Write a custom server only when you need to expose proprietary internal systems
Which AI tools support MCP? Claude Code, Claude Desktop, Cursor, Windsurf, Cline, Zed, and a growing list of AI development tools have added MCP client support

How MCP Compares

MCP occupies a unique position — it's a protocol, not a product. Unlike tool-specific plugin systems (ChatGPT plugins, Cursor's built-in integrations), MCP is vendor-neutral and open-source. A server written for Claude Code works identically in Cursor or any other MCP-compatible client. The closest analogy is LSP (Language Server Protocol), which standardized how editors communicate with language tooling — MCP does the same for AI-to-tool communication.

MCP

MCP (Model Context Protocol) — Everything You Need to Know

Latest Developments

Key Features and Capabilities

Common Questions

How MCP Compares

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