Integrating Large Language Models (LLMs) with custom data sources requires writing extensive function definitions and implementing them manually. This process has to be repeated for every use case, making developing real-time AI applications with two-way communication cumbersome. Model Context Protocol (MCP), released by Anthropic, offers a standard way to connect AI systems with their data sources, eliminating the need for repetitive coding.
By organizing the fragmented data connection to LLMs, MCP can boost the efficiency and possibilities of AI-powered systems. As an open-source project not limited to Anthropic's models, it can become a universal standard for connectivity to LLMs.
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