MCP (Model Context Protocol) is a promising standard that simplifies data integration for AI applications, but it still needs to evolve.

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.

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.

We're announcing native support for Model Context Protocol (MCP) in Windows, enhancing the integration of applications and services.

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

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

The name 'Model Context Protocol' has caused some confusion, with people often mixing it up with other acronyms like MPC or NPC, leading to questions about its purpose.

The main components of MCP include tools for actions the model can take, resources for raw data ingestion, and prompts for user-defined context input.

As AI models become more intelligent, they will be able to handle longer-running tasks, making certain MCP primitives more relevant.