What is MCP

MCP (Model Context Protocol) is an open-source standard for connecting AI applications to external systems.

Using MCP, AI applications like Claude or ChatGPT can connect to data sources (e.g. local files, databases), tools (e.g. search engines, calculators) and workflows (e.g. specialized prompts)—enabling them to access key information and perform tasks.

Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect electronic devices, MCP provides a standardized way to connect AI applications to external systems.

What can MCP enable?

Agents can access your Google Calendar and Notion, acting as a more personalized AI assistant.

Claude Code can generate an entire web app using a Figma design.

Enterprise chatbots can connect to multiple databases across an organization, empowering users to analyze data using chat.

AI models can create 3D designs on Blender and print them out using a 3D printer.

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Why does MCP matter?

Depending on where you sit in the ecosystem, MCP can have a range of benefits.

Developers: MCP reduces development time and complexity when building, or integrating with, an AI application or agent.

AI applications or agents: MCP provides access to an ecosystem of data sources, tools and apps which will enhance capabilities and improve the end-user experience.

End-users: MCP results in more capable AI applications or agents which can access your data and take actions on your behalf when necessary.

The Model Context Protocol includes the following projects:

MCP Specification: A specification of MCP that outlines the implementation requirements for clients and servers.

MCP SDKs: SDKs for different programming languages that implement MCP.

MCP Development Tools: Tools for developing MCP servers and clients, including the MCP Inspector

MCP Reference Server Implementations: Reference implementations of MCP servers.

MCP follows a client-server architecture where an MCP host — an AI application like Claude Code or Claude Desktop — establishes connections to one or more MCP servers. The MCP host accomplishes this by creating one MCP client for each MCP server. Each MCP client maintains a dedicated connection with its corresponding MCP server.

Local MCP servers that use the STDIO transport typically serve a single MCP client, whereas remote MCP servers that use the Streamable HTTP transport will typically serve many MCP clients.

The key participants in the MCP architecture are:

MCP Host: The AI application that coordinates and manages one or multiple MCP clients

MCP Client: A component that maintains a connection to an MCP server and obtains context from an MCP server for the MCP host to use

MCP Server: A program that provides context to MCP clients

For example: Visual Studio Code acts as an MCP host. When Visual Studio Code establishes a connection to an MCP server, such as the Sentry MCP server, the Visual Studio Code runtime instantiates an MCP client object that maintains the connection to the Sentry MCP server. When Visual Studio Code subsequently connects to another MCP server, such as the local filesystem server, the Visual Studio Code runtime instantiates an additional MCP client object to maintain this connectio

Note that MCP server refers to the program that serves context data, regardless of where it runs. MCP servers can execute locally or remotely. For example, when Claude Desktop launches the filesystem server, the server runs locally on the same machine because it uses the STDIO transport. This is commonly referred to as a “local” MCP server. The official Sentry MCP server runs on the Sentry platform, and uses the Streamable HTTP transport. This is commonly referred to as a “remote” MCP server.