What is MCP? (Model Context Protocol)
MCP — the Model Context Protocol — is an open standard that defines how AI models connect to external tools, data sources, and services. It's the "USB-C for AI" — a universal plug that any AI agent can use to interact with any tool.
Definition
The Model Context Protocol (MCP) is a standardized communication protocol that allows AI models to interact with external systems — databases, APIs, file systems, and other tools — in a consistent, secure, and discoverable way.
Before MCP, every AI tool integration required custom code. A tool that worked with GPT wouldn't work with Claude. MCP solves this by providing a universal interface: write your tool once, and any MCP-compatible AI model can use it.
Architecture
MCP uses a client-server model:
- MCP Host: The application running the AI model (e.g., Claude Desktop, an IDE plugin, a custom agent)
- MCP Client: Connects to servers and routes requests from the AI model
- MCP Server: Exposes tools, resources, and prompts to clients
- Transport: Communication layer (stdio for local, SSE for remote)
An MCP server exposes three types of capabilities: Tools (functions the AI can call), Resources (data the AI can read), and Prompts (pre-configured prompt templates).
Transport Methods
stdio (Local)
Communication via standard input/output. Used for local tools running on the same machine as the AI model. Fast, secure, no network overhead.
SSE (Remote)
Server-Sent Events over HTTP. Used for remote tools and cloud services. Enables connecting to MCP servers anywhere on the internet.
Common Use Cases
- 📊 Data Access: Let AI agents query databases and read files
- 🔧 Tool Integration: Enable agents to use APIs, run code, execute commands
- 🌐 Web Interaction: Browse websites, fetch URLs, interact with web apps
- 📄 Document Processing: Read, write, and transform documents
- 🤖 Multi-Agent Communication: Agents sharing context via A2A (built on MCP concepts)
MCP vs REST APIs
REST APIs were designed for human developers building applications. MCP is designed for AI agents that need to discover and use tools dynamically.
| Aspect | REST API | MCP |
|---|---|---|
| Discovery | Manual (read docs) | Automatic (server advertises tools) |
| Schema | OpenAPI/Swagger | JSON Schema (built-in) |
| Authentication | Per-API (API keys, OAuth) | Protocol-level |
| Cross-Model | No (custom per model) | Yes (any MCP-compatible model) |
Getting Started with MCP
The easiest way to start with MCP is to explore existing servers on SkillExchange. Use our free MCP Tester to try servers, or browse the MCP Servers directory.
Want to build your own MCP server? Read our step-by-step tutorial or check the developer documentation.