MCP (Model Context Protocol) is an open-source standard that lets AI applications connect to outside data, tools and workflows. The official documentation compares it to a USB-C port: one standard plug instead of a custom cable for every pair of devices. This guide summarizes the introduction page on modelcontextprotocol.io as read on 22 October 2026.
The short answer
- What it is: an open-source standard for connecting AI applications to external systems.
- What it connects: data sources such as local files and databases, tools such as search engines and calculators, and workflows such as specialized prompts.
- Who supports it: AI assistants such as Claude and ChatGPT, and development tools such as Visual Studio Code, Cursor and MCPJam.
- Why it exists: “Build once and integrate everywhere”. One standard replaces a custom connection for each pair of app and system.
What can MCP enable?
The documentation gives four examples:
- Agents that access your Google Calendar and Notion.
- Claude Code generating a web app from a Figma design.
- Enterprise chatbots connecting to several databases, so users can analyze data by chat.
- AI models creating 3D designs in Blender and printing them on a 3D printer.
Who benefits from MCP?
- Developers: MCP reduces development time and complexity when building or integrating an AI application or agent.
- AI applications and agents: they get access to an ecosystem of data sources, tools and apps.
- End users: more capable AI applications that can access their data and take actions on their behalf when necessary.
How do you start with MCP?
The documentation points to three build paths:
- Build servers: expose your data and tools.
- Build clients: applications that connect to servers.
- Build MCP Apps: interactive apps that run inside AI clients.
If you only want to use MCP, not build it, you do not need any of these. You only need an assistant or tool from the supported list. The documentation also links pages on architecture and on security best practices.
What should you check before connecting a server?
The documentation notes that MCP lets AI applications access user data and take actions. That is why it has a security page. We suggest you check what data a server can read and what actions it can take before you connect it to an assistant.
What to do next
- Open the introduction page on modelcontextprotocol.io and pick one of the three build paths if you build software.
- Read the security best-practices page before you connect any server.
- If you are a user, start with one server and one data source, then widen access only if you need it. This is our suggestion.
Questions and answers about MCP
Is MCP only for Claude?
No. The documentation lists Claude and ChatGPT among supporting assistants, along with tools such as Visual Studio Code and Cursor.
Is MCP free to use?
The standard itself is open source. Each server and AI app sets its own pricing, so check the product you plan to connect.
What can an MCP connection reach?
Data sources, tools and workflows. Check what a specific server can read and do before you connect it.
Why does MCP matter for developers?
It cuts the work of integrating an AI application or agent with many systems, because one standard replaces a custom connection for each pair.
Where do I read about MCP security?
The introduction page links a Security page on best practices. Read it before you connect any server.
Terms in plain language
- Protocol: an agreed set of rules two programs use to talk to each other.
- MCP server: a program that exposes data and tools to AI applications.
- MCP client: an application that connects to servers.
- Agent: an AI program that can take actions, not only answer questions.
Sources
Facts read on 22 October 2026. We did not build or install an MCP server for this guide.
