OneTool MCP server

<!-- mcp-name: io.github.beycom/onetool-mcp -->

🧿 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%"

— Anthropic Engineering

97% fewer tokens. 30× lower cost. No context rot. (Measured - 47,660 → 1,131 input tokens against 18 MCP servers.)

📖 Read the full story

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)

Three packs, one request. Intermediate results flow between tools as variables - the page body never touches your context window, and the summarising runs on a cheap model instead of your expensive coding agent.

Every call is explicit and reviewable - __onetool brave.search(query="...") shows you exactly what runs. No tool-selection guessing.

And the runtime is built for how agents actually type:

• mem.search(q="auth") works - any unambiguous parameter prefix resolves (q= → query=)
• wb.draw(...) works - packs have short aliases (wb, ctx, img)
• github.listRepositories() works on proxied servers - snake/camel/Pascal all resolve
• A typo'd tool gets a did-you-mean, a disconnected server names the command that fixes it
• Oversized results come back as a searchable handle instead of flooding the window

Install

Bootstrap (installs uv if missing, installs OneTool, initialises config, prints MCP config):

Shortened. The full README is on GitHub.