Model Context Protocol (MCP)

An open standard that lets any AI application connect to tools and data sources through a shared interface, so you build the integration once and every compatible app can use it.

MCP is an open standard that lets any AI application connect to tools and data sources through a shared interface, so you build the integration once and every compatible app can use it. You set up a server that exposes your tools and data, and any compatible AI application (Claude, ChatGPT, Cursor, coding agents, custom apps) can discover and use them through the same protocol. Before MCP, every AI tool needed its own custom code to connect to your files, databases, calendars, or APIs.

Builder example

Build one MCP server for your company's data and every AI tool your team uses can access it without separate integration work. This is especially powerful when your team uses multiple AI applications: write the connector once, get access everywhere. The tradeoff is that anything your server exposes becomes available to any connected AI, so scope access carefully.

You want Claude, Cursor, and another agent to query the same project notes without rebuilding the integration three times.

Expose the notes through a Model Context Protocol (MCP) server, then keep permissions narrow and version the server contract.

Common confusion: MCP handles the connection, not the security. The tool descriptions and data that flow through it become part of what the AI trusts and acts on. A poorly scoped server can give an agent far more access than you intended.