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Developer creates TOON format to cut LLM token waste by 83%

A developer has created a command-line tool called `mcptoon` to reduce token waste in interactions with Large Language Models (LLMs) like Claude, GPT-4, and Gemini. The tool converts standard JSON output into a more compact format called TOON (Token-Optimized Object Notation), which removes unnecessary structural syntax such as braces, quotes, and commas. This optimization, verified with the `tiktoken` tokenizer, can significantly reduce token usage, with measured savings of up to 83% in some cases, without compromising the LLM's ability to parse the structured data. `mcptoon` also includes safety features like credential leak detection and blocking dangerous operations. AI

IMPACT Reduces operational costs for AI agents by optimizing token usage and improving efficiency in LLM interactions.

RANK_REASON The item describes a new command-line tool that optimizes LLM interaction by creating a new data format.

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Developer creates TOON format to cut LLM token waste by 83%

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  1. dev.to — MCP tag TIER_1 English(EN) · MCP Token Saver ·

    I measured MCP token waste. Then I wrote a CLI to fix it.

    <p>I use MCP servers with Claude Code every day. Last week I counted the tokens.</p> <p>5 servers, 96 tools. The JSON tool listing: 2,034 tokens. Before I've typed a single character.</p> <p>Then 20 tool calls, each response wrapped in <code>{"content":[{"type":"text","text":"...…