mcptoon

Install 1,000 skills and 1,000 MCP tools locally — and don't worry about the token context. mcptoon manages it all.

Its own compact format saves 99.2% of tokens; no line of config to write for any desktop or command-line agent.

Connects to a 17,000+ MCP tool registry and searches skills on demand — nothing pre-installed, you pick what goes in.

It's just a 227KB native CLI — delete it anytime; keep it, and you never have to configure tools or skills for any agent again.

👉 See it first: landing page · 30-second token calculator · 中文

👉 Or run it: pip install mcptoon && mcptoon bench — it measures what your own tools and skills cost, on your machine.

👉 Developer docs · Contributing · Issues

Why mcptoon

Every MCP agent (Claude Code, Cursor, Codex, …) loads the full description of every tool and every skill into its context window before it does any work — and re-sends it every turn. On 255 tools that is 71,929 tokens: more than half of a 128K window spent on descriptions, before the first question.

How the token saving works

mcptoon keeps those descriptions on disk, not in context, and hands the agent a compact view instead:

• A name index, not full schemas. Picking a tool only needs its name — 255 tools become 581 tokens (−99.2%). The full schema is fetched on demand with mcptoon inspect, only when a tool is actually called.
• Skills the same way. One resident pointer (39 tokens) plus one lookup (501 tokens) replaces loading every SKILL.md in full — 926,232 → 39 + 501 (−99.9%).
• Results too. --toon encodes a tool's result ~34% smaller than JSON.

Nothing is lost: the full schema and the full skill text stay one command away. Only the context window is spared.

mcptoon is a 227KB, zero-dependency native CLI that manages every MCP tool and agent skill on your computer — and shares them across all your agents with no config written by you.

This isn't just us talking

Those numbers are ours — but "loading every tool schema into context is expensive" is not a claim only we make:

• Anthropic's engineering write-up — tool schemas flooding the context window is a real cost; one example drops from 150,000 tokens to 2,000
• Firecrawl's benchmark — the same task cost 1,365 tokens via CLI vs 44,026 via MCP (32×)
• Scalekit's benchmark — CLI 10–32× cheaper, 100% reliable vs MCP's 72%
• MCP-Zero (arXiv:2506.01056) — on-demand tool retrieval, near-constant cost regardless of tool count

mcptoon is the one you can use today, covering every agent at once.

Two ways in

Install once, and every desktop AI you have — Claude Desktop, Claude Code, Codex, Cursor, Windsurf, Cline, VS Code Copilot and any other agent — shares all the tools and skills you already have. You write nothing in any agent's config.

→ Install and go

Script it. mcptoon is a plain CLI with stable JSON output and an mcptoon serve MCP endpoint — wire it into your own agent, CI, or app.

→ Commands and formats

Reproduce the numbers yourself: pip install mcptoon && mcptoon bench

Skills work the same way: 926,232 tokens of SKILL.md text → 39 resident + 501 per lookup (−99.9%). Call results shrink another ~34% with --toon.

Path 1 · I just use AI tools

You have a desktop AI — Claude, Codex, Cursor, Windsurf, Cline, VS Code Copilot. Today, adding a tool or a skill means hand-editing that agent's JSON. mcptoon removes that step:

1. Install once.

   pip install mcptoon && mcptoon quickstart
   

   quickstart finds your MCP servers, writes your config, and registers mcptoon in every agent it detects. (Skip quickstart and the first command you run still self-heals: it installs mcptoon's own skill into each agent and builds the skill index, once per machine.)

2. Add tools and skills in one place — here, not in each agent.

   mcptoon install --search github     # find and install any MCP server
   mcptoon skills search "make a PDF"  # find a skill by what it does
   

3. Use them from any agent. Your agent runs mcptoon like any other command — no config, no restart. See Works with every AI agent.

Want a head start? Four built-in starter packs — essentials, web-research, code-review, docs — stand up a working toolset in one command:

mcptoon install --pack essentials

Path 2 · I build with MCP / agents

mcptoon is a plain CLI with scriptable output, plus an MCP endpoint when you want one.

mcptoon manifest --format json      # machine-readable tool index
mcptoon call <server> <tool> '{}'   # call any tool, JSON or --toon output
mcptoon serve                       # expose every configured server behind one MCP endpoint

• Stable output — JSON by default, --toon for ~34% smaller results, --format mcp to export standard MCP JSON.
• mcptoon serve — stdio or HTTP, connection pooling, per-agent keys, for clients that insist on a proxy.
• Zero dependencies — pure Python standard library, so it drops into any environment (CI, containers, air-gapped).

Full reference: DEVELOPERS.md and All commands.

Contents

• Why mcptoon
• How the token saving works
• This isn't just us talking
• Two ways in
• 30 seconds up and running
• What it does
• Where the tools come from
• The three bills
• Install
• Works with every AI agent
• Why a CLI, not a proxy
• All commands
• Trust and safety
• Credits and references
• Contributing
• License

30 seconds up and running

pip install mcptoon                          # pure stdlib, 227KB, zero dependencies

# One command: find your MCP servers, write your config, register the gateway
# in every agent you have, and show you what it found:
mcptoon quickstart

# See every tool available (names-only by default; 255 tools cost 581 tokens):
mcptoon manifest

# Call a tool (JSON output by default; add --toon to save more):
mcptoon call everything echo '{"message":"hi"}'

quickstart is also what makes mcptoon visible: it writes mcptoon serve int