The Model Context Protocol (MCP) could reshape how software operates by providing a framework for better context and memory management in AI applications.

MCP is a way to integrate workflows into AI applications simply, providing context to applications that use large language models (LLMs).

MCP standardizes how data is taken from various sources, like APIs or internal data, and provided to the model, ensuring a consistent interaction pattern.

The hope is that MCP effectively addresses the need for providing context to large language models (LLMs) and that the community will help guide its future development. The Model Context Protocol (MCP) is designed to evolve with community input, ensuring it meets the needs of users.

The MCP product emerged from engineers recognizing the need for a standardized protocol to better interact with models, rather than a top-down directive.

MCP has become an industry standard for integration protocols, with many companies now adopting it into their products and creating servers to connect with various clients.

Making MCP an open-source standard was a key decision to reduce friction for integration builders and encourage investment in AI applications.

We launched the Model Context Protocol (MCP) around Thanksgiving in November 2024, and the initial reception was slow as many people were unsure about what MCP was.

MCP has rapidly gained traction because it fills a crucial niche in the open agentic web ecosystem, functioning similarly to HTTP by allowing sophisticated actions without imposing strict payload opinions.