AI EncyclopediaAgents & protocols
Model Context Protocol (MCP)
An open standard, created by Anthropic and released in November 2024, for connecting AI applications to external data sources and tools through one common protocol instead of a custom integration for each pairing.
In plain English
Before MCP, connecting an AI assistant to your company's files, Slack or database meant building a separate, bespoke integration for every single combination of AI tool and data source. MCP is a shared plug shape both sides can build to once, the way USB replaced a drawer full of proprietary cables.
Technical explanation
MCP enables secure, two-way connections between data sources and AI applications. Developers either expose data through MCP servers or build AI applications (MCP clients) that connect to them. Anthropic open-sourced MCP on 25 November 2024, led by David Soria Parra and Justin Spahr-Summers, releasing the specification and SDKs, local server support in the Claude Desktop app, and an open-source repository of pre-built servers for systems including Google Drive, Slack, GitHub, Git, Postgres and Puppeteer.
Why it matters
Even the most capable model is limited by what it can actually see and act on. MCP addresses that by standardising how an AI system connects to the data and tools it needs, rather than leaving every integration to be built from scratch per vendor pair - it has since been adopted across the industry well beyond Anthropic's own products.
Real-world example
Early adopters at launch included Block and Apollo integrating MCP into their internal systems, and development-tool makers Zed, Replit, Codeium and Sourcegraph working with Anthropic to enhance their platforms with MCP support.
Common misunderstanding
That MCP is a feature specific to Claude. It is an open, published protocol and SDK set, not a proprietary Claude-only integration - any AI application can implement an MCP client, and any data source can expose an MCP server.
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