Why This Matters
The article highlights the limitations of MCP (Model Context Protocol) in connecting LLMs to external tools, particularly its significant consumption of the model's context window, which hampers efficiency and reliability. Recent improvements, like Claude Code's Tool Search with Deferred Loading, have mitigated some issues, but the core challenges remain relevant for the industry. This underscores the need for more efficient integration methods to optimize LLM performance and developer workflows.
Key Takeaways
- MCP consumes a large portion of the LLM's context window, reducing available space for tasks.
- Recent updates have improved tool loading efficiency, but core issues persist.
- Developers are reconsidering MCP's role, favoring more reliable and less resource-intensive solutions.
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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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