Why MCP Was Always a Bad Idea? (maharship.com)

A recent analysis critiques the Model Control Protocol (MCP), originally introduced by Anthropic in November 2024 for enabling AI agents to connect with external services. While MCP saw rapid adoption alongside the growth of large language models (LLMs), it has become increasingly inefficient as AI capabilities have advanced significantly. The analysis highlights issues like context bloat, where multiple MCP servers overwhelm model inputs, and notes that LLMs can now autonomously call APIs and execute code without intermediary protocols. This evolution has prompted suggestions to phase out MCP in favor of standardizing direct access to documented HTTP APIs and command-line interfaces (CLIs). The significance of this discussion lies in the transition towards more efficient AI workflows as models have become adept at managing tasks autonomously. The recommendation to eliminate MCP servers suggests a shift towards leveraging established web protocols, which can simplify interactions and potentially enhance performance. Key technical implications include encouraging the adoption of headers for content negotiation—like the 'Accept: text/markdown' header for streamlined responses—which could improve the efficiency of communication between AI agents and external services. This shift signifies a critical evolution in the AI/ML landscape, emphasizing the need for protocols that align with contemporary technological capabilities.