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og:description: mcptoon is a zero-dependency Python CLI client for the Model Context Protocol (MCP) that dramatically reduces token consumption. Standard MCP tool discovery...
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# GitHub - activeing123/mcptoon: Token-efficient MCP CLI client. 97% less tokens on tool discovery, 40-60% on results. Zero deps. Cross-platform. Works with every AI agent.

**[Hacker News](https://daily.dev/sources/hn)** · 7 min read · 1 upvotes · 0 comments

## Summary

mcptoon is a zero-dependency Python CLI client for the Model Context Protocol (MCP) that dramatically reduces token consumption. Standard MCP tool discovery for 96 tools costs ~10,000 tokens in JSON; mcptoon outputs TOON (Token-Optimized Object Notation) and cuts that to ~350 tokens — a 97% reduction. Tool call results see 40-60% savings. It works with any AI agent that can run shell commands (Claude Code, Codex, Cursor, OpenCode, etc.), supports both stdio and HTTP MCP servers, includes a 5-minute schema cache, local usage tracking, dangerous-operation blocking, and a Python API. The entire package is ~50KB, ~1,700 lines, and imports nothing outside the Python standard library.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://github.com/activeing123/mcptoon>

## Questions this post answers

### How can I reduce the token overhead of MCP tool discovery in my AI agent setup?

A CLI client called mcptoon connects to MCP servers over stdio or HTTP and outputs a compact TOON (Token-Optimized Object Notation) format instead of raw JSON, cutting tool discovery from around 10,000 tokens to roughly 350. It reports 97% savings on tool discovery for 96 tools and 40-60% savings on tool call results, with zero third-party dependencies and a 50KB install size.

_Developers tuning agent context budgets can track MCP tooling changes like this on daily.dev._

### What is TOON format and how does it differ from JSON for representing data compactly?

TOON (Token-Optimized Object Notation) replaces JSON's braces, quotes, and colons with pipes, uses spaces instead of brackets and commas for arrays, represents true/false as single characters T/F, null as the symbol ∅, and compacts nested objects recursively, such as turning {"a":{"b":[1,2]}} into a:b:1_2, cutting token counts by roughly 40-60% for structured data.

_Anyone comparing data serialization formats for LLM token efficiency can follow shifts like TOON on daily.dev._

### How does mcptoon compare to mcp-cli or mcporter for using MCP tools across different AI agents?

Mcptoon works with any AI agent that can run shell commands, including Claude Code, Codex, OpenCode, and Cursor, using one shared config, while mcp-cli and mcporter are limited to Claude only. Mcptoon has zero dependencies and a ~50KB install versus mcp-cli's ~50MB+ and 5-20 dependencies, and it adds dangerous-operation blocking, local usage tracking, and a 5-minute schema cache that the alternatives lack.

_Developers weighing MCP client tooling options can compare choices like these on daily.dev._

## Similar posts on daily.dev

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- [Your MCP Server Is Eating Your Context Window. There's a Simpler Way](https://daily.dev/posts/your-mcp-server-is-eating-your-context-window-there-s-a-simpler-way-vhhujbvmb) · Hacker News · 2 upvotes · 1 comments
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---

Tags: [#ai](https://daily.dev/tags/ai), [#python](https://daily.dev/tags/python), [#ai-agents](https://daily.dev/tags/ai-agents), [#claude](https://daily.dev/tags/claude)

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