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MCP Is Dead

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Why This Matters

The article highlights the limitations of MCP (Model Context Protocol), emphasizing how it consumes significant portions of the LLM's context window, leading to inefficiencies and reduced reliability. With recent improvements like Claude Code's Tool Search, some issues are mitigated, but the core architectural concerns remain relevant for the future of AI tool integration.

Key Takeaways

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Reference: MCP is dead. Long live the CLI

After reading the above article, we ran the experiments on our actual stack. This document covers the original argument, additional research, and our measurements.

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Update: Since these measurements were taken, Claude Code has rolled out Tool Search with Deferred Loading, which loads MCP tool schemas on-demand and reduces context usage by 85%+. The context bloat described in Problem 1 is largely addressed for users on current Claude Code versions. The performance, debugging, and architectural arguments below still apply.

What's Wrong with MCP

MCP (Model Context Protocol) connects LLMs to external tools (GitHub, Linear, Notion, Slack, etc.).

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