Anthropic's new Model Context Protocol enables a standardized connection of external services to language models for the first time - and could transform the entire industry.
Modern language models such as GPT-4o or Claude achieve impressive things, but they come up against a fundamental limit: as complex mathematical functions, they cannot interact with the outside world on their own. This isolation considerably limits their possible applications.
The Model Context Protocol (MCP) addresses this problem by providing an open, standardized approach for connecting external tools to AI models. In contrast to proprietary solutions such as OpenAI's "Function Calling", MCP creates a vendor-independent alternative that is accessible to all AI models and services.
The protocol defines three main actors:
Communication takes place via a standardized manifest that describes the capabilities of the MCP server and enables the host to make these available to the model as a context.
MCP establishes a modular architecture that enables AI models to access any external resources - from databases and email services to webcams and internet searches. Standardization promises to drastically simplify integrations, as developers only have to implement one interface.
The protocol could mark a turning point for the AI ecosystem. It eliminates the need for proprietary connections and enables a universal, modular AI working environment. Experts expect numerous server products to implement MCP as standard in the future - with far-reaching consequences for the entire industry.