Model Context Protocol
Model Context Protocol
An important open standard for connecting AI assistants to a business's data and software.
The official MCP documentation site, an open standard for connecting AI assistants to external data and tools.
Overview
Model Context Protocol (MCP) is an open, open-source standard that defines how AI applications connect to external systems such as files, databases, search tools or workflows. The official site compares MCP to a USB-C port for AI: one common kind of connection in place of dozens of individual integrations.
MCP works on a client-server model. An AI application (host) such as Claude, ChatGPT, VS Code or Cursor creates one client for each MCP server it connects to. A server can run locally on your machine (over stdio) or remotely (over Streamable HTTP).
For businesses, the practical meaning is this: build one MCP server for your internal data or software, and many different AI applications can reuse it, letting AI assistants look up information and act on staff's behalf when permitted.
Highlights
Open, shared standard
One standard supported by many AI applications and coding tools; build once, use in many places.
Three main server-side components
Tools (functions for the AI to execute), Resources (data as context) and Prompts (reusable prompt templates).
Local or remote
Local servers communicate over stdio on the same machine; remote servers use Streamable HTTP and support authentication, with OAuth recommended.
JSON-RPC 2.0 foundation
All messages between client and server use the JSON-RPC 2.0 format, making them easy to inspect and debug.
User-centered
The documentation emphasizes obtaining user consent before sharing data or calling tools.
Full ecosystem
Includes the specification, SDKs for many languages, the MCP Inspector tool and a set of reference servers.
What it's for
AI assistant reading internal data
Connect AI to document folders or databases so staff can ask questions in natural language.
Data analysis chatbot
Let an internal chatbot query the company's multiple data sources to compile reports through a chat window.
Personalized assistant
Give AI access to work calendars and note-taking tools to schedule and send reminders based on real context.
Faster developers
Bring designs, code repositories or bug trackers into AI-powered coding tools for seamless work.
Standardizing AI integration
Instead of writing a separate connection for each AI app, the business builds one shared MCP server.
How to use it
- 1
Read the architecture section
Learn the concepts of host, client, server and the three components tools, resources and prompts on the documentation site.
- 2
Try an existing server
Install a reference server into the AI app you use to see how MCP works.
$npx -y @modelcontextprotocol/server-memory - 3
Identify the data to connect
List the internal systems you want AI to access and the minimum permissions to grant.
- 4
Build your own server with an SDK
Use the official SDKs (Python, TypeScript...) following the Build servers guide on the homepage.
- 5
Test and review security
Use MCP Inspector to try the server and read the Security best practices section before deploying.
Video guides
The Model Context Protocol (MCP)
Anthropic
How Model Context Protocol (MCP) actually works
Google Cloud Tech
Giải thích MCP siêu đơn giản và hướng dẫn kết nối MCP Server
Việt Nguyễn AI
Real-world example
An office equipment distributor in Da Nang keeps its product catalog and inventory in an internal database. The IT team builds an MCP server that provides an inventory lookup tool and a resource describing the data structure. Sales staff use an MCP-capable AI app to quickly ask which items are in stock, and each time the AI calls a tool, a confirmation request appears before it runs.
Tips & notes
Start with read-only access
Give AI read-only access to data first, and open write access only once well controlled.
Treat tools as real code execution
The specification notes that tools can execute arbitrary code, so always require confirmation and limit scope.
Prefer trustworthy servers
Tool descriptions from unfamiliar servers should be treated as untrusted until verified.
Track the specification version
MCP is updated by date-based versions, so check which version your apps and SDKs support.
FAQ
Is MCP a paid product?
No, MCP is an open-source open standard. Any costs come from the AI application or services you connect.
Which applications support MCP?
The official site lists Claude, ChatGPT, Visual Studio Code, Cursor, MCPJam and many more.
Can I use it without knowing how to code?
You can use ready-made servers in AI apps, but building a server for internal data requires a developer.
Does MCP manage the AI model itself?
No. MCP only handles the exchange of context and does not dictate how an application uses language models.
Useful links
Want to apply this in your business?
2dm looks at your workflows, picks the right tools and sets them up with your team. The first call is free.
Same topic
MCP Servers
4.5
A repository of reference MCP servers and a list of community-built servers.
MCP specification
3.5
The full technical specification of the protocol: tools, resources, prompts and how clients and servers communicate.
MCP Registry
3.5
The official directory for finding and publishing MCP servers.