beycom/onetool-mcp
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🧿 One MCP for developers - no tool tax, no context rot. 100+ tools including Brave, Google, Context7, Excalidraw, AWS, Version Checker, Excel, File Ops, Database, Playwright, Chrome DevTools and...
概要
🧿 One MCP for developers - no tool tax, no context rot. 250+ tools your agent calls as Python code: search, docs, files, databases, diagrams, vision, memory - plus a proxy for every MCP server you already use. Works with Claude Code, Cursor, Codex - any MCP client Every MCP server re-sends its tool definitions on every request: . Connect 5 servers and you've burned 55K tokens before the conversation starts. Connect 10+ and you're at 100K. The math is brutal: Claude Opus 4.5 at $5/M input tokens, 20 days × 10 conversations × 10 messages × 3K tokens = - even if you never use the tools. And then there's - your AI literally gets dumber as you add more tools (Chroma Research, 2025). OneTool is that exposes tools as a Python API. Instead of reading tool definitions, your agent writes code: Configure one MCP server. Use unlimited tools - ~2K tokens no matter how many you add. "Agents scale better by writing code to call tools instead.
README
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🧿 One MCP for developers - no tool tax, no context rot.250+ tools your agent calls as Python code: search, docs, files, databases, diagrams, vision, memory - plus a proxy for every MCP server you already use.
Works with Claude Code, Cursor, Codex - any MCP client
The Problem
Every MCP server re-sends its tool definitions on every request: 3K-30K tokens each. Connect 5 servers and you’ve burned 55K tokens before the conversation starts. Connect 10+ and you’re at 100K.
The math is brutal: Claude Opus 4.5 at $5/M input tokens, 20 days × 10 conversations × 10 messages × 3K tokens = $30/month per MCP server - even if you never use the tools.
And then there’s context rot - your AI literally gets dumber as you add more tools (Chroma Research, 2025).
The Solution
OneTool is one MCP server that exposes tools as a Python API. Instead of reading tool definitions, your agent writes code:
__onetool brave.search(query="react 19 server components")
Configure one MCP server. Use unlimited tools - ~2K tokens no matter how many you add.
“Agents scale better by writing code to call tools instead. This reduces the token usage from 150,000 tokens to 2,000 tokens…a cost saving of 98.7%”
97% fewer tokens. 30× lower cost. No context rot. (Measured - 47,660 → 1,131 input tokens against 18 MCP servers.)
Code Is the Interface
Because tools are Python functions, your agent does things tool-call JSON can’t: batch, chain, loop, compose.
__onetool
page = webfetch.fetch(url="https://fastmcp.dev/changelog", output_format="markdown")
notes = ot_llm.transform(data=page, prompt="Summarise the breaking changes")
mem.write(topic="deps/fastmcp", content=notes)
インストール
npx skills add https://github.com/beycom/onetool-mcp --skill ot-ref --agent claude