Model Context Protocol (MCP) — what is it ?

The Model Context Protocol (MCP) is like a rulebook that helps different AI systems talk to each other clearly. It tells them how to share important background information (called context) so they all understand things the same way.

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Think of it like giving instructions to a new team member — MCP makes sure everyone uses the same format and language, so nothing gets lost or misunderstood.

Key Features

• Standardized Format: MCP defines a shared schema for what “context” looks like (e.g., conversations, documents, past interactions).
• Tool-Agnostic: It is not tied to any specific AI model or provider, making it easier to integrate into any ecosystem (e.g., OpenAI, Anthropic, Hugging Face).
• Composable: You can plug in different memory systems, context providers, or agents as long as they follow the protocol.
• Interoperability: MCP enables smooth interactions between memory, retrieval-augmented generation (RAG) systems, agents, and LLMs.

Who Is Behind MCP?