MCP explained
The Model Context Protocol is the standard way to connect AI assistants to tools and data. Before adopting it, most people ask how it relates to something they already use. Each page below answers one of those questions, plainly, with a side-by-side table.
- MCP vs API
An API is a contract for software a developer writes against. MCP is a contract for AI models: the server describes its tools so a model can find and call them without anyone writing integration code. Most MCP servers call an API underneath.
- MCP vs RAG
RAG (retrieval-augmented generation) finds relevant documents and puts them in the prompt. MCP is a standard way for a model to call tools, one of which can be a retrieval tool. RAG is the what; MCP can be the how.
- MCP vs CLI
If the agent has a shell and the tool has a good CLI it already knows, the CLI is often cheaper and simpler. MCP wins when there is no shell, when you need scoped auth or a remote service, or when you want typed tools and per-tool permissions.
- MCP vs A2A
MCP is agent-to-tool: a model calls functions and reads data through a server. A2A (Agent2Agent) is agent-to-agent: one autonomous agent hands a task to another and gets results back. A travel agent uses MCP to search flights and A2A to ask a separate expenses agent to file the receipt.
- MCP vs Agent Skills
An Agent Skill is a folder of instructions, scripts and files (a SKILL.md) that teaches an agent how to do a task, loaded only when relevant. An MCP server gives the agent access to an outside system. A skill might say how your team writes release notes; an MCP server lets the agent read the merged pull requests to write them from.
- MCP vs function calling
Function calling is a model ability: given function definitions, the model outputs a structured call. MCP is a protocol that supplies those definitions from a separate server and runs the call there. MCP tools are invoked through the model's function calling.
- MCP vs LangChain
LangChain (with LangGraph) is a framework for writing LLM applications and agents in Python or JavaScript. MCP is a protocol for connecting any agent to tools. A LangChain agent can load MCP servers as its tools through LangChain's MCP adapters.
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