What MCP is, in one paragraph
The Model Context Protocol is an open standard, first published by Anthropic in November 2024, for connecting AI applications to outside tools and data. An MCP server describes what it can do (tools the model can call, resources it can read, prompt templates) in a machine-readable way, and any MCP client, such as Claude, Cursor, VS Code or ChatGPT, can connect to it without custom glue code. Messages are JSON-RPC 2.0, sent over standard input and output for a local server or over HTTP for a remote one.
What LangChain is
LangChain is an open-source framework for building applications on language models: prompts, model calls, retrieval, memory and agents, with hundreds of integrations. LangGraph, from the same team, is its library for stateful, multi-step agents. You write code with it; it runs inside your application.
Different layers
LangChain decides how your agent thinks and flows: which model, what prompt, what happens after each step. MCP decides how any agent reaches a tool.
Before MCP, a LangChain tool integration worked only inside LangChain. An MCP server works in LangChain and also in Claude, Cursor, VS Code and every other MCP client. That is why many integrations are now written once as MCP servers and consumed from frameworks.
Using them together
LangChain publishes MCP adapters that connect to one or more MCP servers and turn their tools into LangChain tools, so a LangGraph agent can use them like any other. The usual setup: build the agent's logic in LangChain or LangGraph, and get its tools from MCP servers you can also reuse elsewhere.
What to check
Loading an MCP server into your agent gives the agent whatever the server's tools can do, inside your application's permissions. Check the server's safety report first: write tools, auth on remote endpoints, install scripts in local packages, and the maintainer behind it.