onetool-mcp

@beycom/onetool-mcp

0 Stars 2 次浏览 beycom 更新于 2026-08-23

馃ЭOne MCP, unlimited tools. Execute Python code with access to curated tool packs.

MCP 服务配置

复制以下 JSON 到 OPClaw 或其他 MCP 客户端的配置文件中即可使用

{
  "mcpServers": {
    "onetool-mcp": {
      "args": [
        "onetool-mcp@1.0.0rc2"
      ],
      "command": "uvx"
    }
  }
}

可用工具（5 个）

该服务在 MCP 协议中暴露的工具，AI 可按需调用

tavily_search 14 个参数需填 1 项 Search the web for current information on any topic. Use for news, facts, or data beyond your knowledge cutoff. Returns snippets and source URLs.

Search the web for current information on any topic. Use for news, facts, or data beyond your knowledge cutoff. Returns snippets and source URLs.

必填参数：query

tavily_extract 6 个参数需填 1 项 Extract content from URLs. Returns raw page content in markdown or text format.

Extract content from URLs. Returns raw page content in markdown or text format.

必填参数：urls

tavily_crawl 11 个参数需填 1 项 Crawl a website starting from a URL. Extracts content from pages with configurable depth and breadth.

Crawl a website starting from a URL. Extracts content from pages with configurable depth and breadth.

必填参数：url

tavily_map 8 个参数需填 1 项 Map a website's structure. Returns a list of URLs found starting from the base URL.

Map a website's structure. Returns a list of URLs found starting from the base URL.

必填参数：url

tavily_research 2 个参数需填 1 项 Perform comprehensive research on a given topic or question. Use this tool when you need to gather information from multiple sources to answer a question or complete a task. Returns a detailed response based on the research findings.

Perform comprehensive research on a given topic or question. Use this tool when you need to gather information from multiple sources to answer a question or complete a task. Returns a detailed response based on the research findings.

必填参数：input

服务介绍

The Problem

Each MCP server consumes 3K-30K tokens per request. Connect 5 servers and you've burned 55K tokens before the conversation starts. Connect 10+ and you're at 100K tokens.

The math is brutal: Claude Opus 4.5 at $5/M input tokens, 20 days 脳 10 conversations 脳 10 messages 脳 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:

__ot brave.search(query="react docs 2026")

Configure one MCP server. Use unlimited tools.

"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%"

鈥� Anthropic Engineering

96% fewer tokens. 24脳 lower cost. No context rot.

馃摉 Read the full story

See It In Action

Demo	Description
Compare the Search	Side-by-side token comparison
Build a Wikipedia Tool	Create a custom tool in seconds

Install

Requires uv:

uv tool install onetool-mcp
onetool init

Add to Claude Code:

claude mcp add onetool onetool

Or manually add to ~/.claude/mcp.json:

{
  "mcpServers": {
    "onetool": {
      "command": "onetool"
    }
  }
}

That's it. All 100+ tools work out of the box.

Verify: onetool init validate

馃摉 Full installation guide

Features

Feature	Description
96% Token Savings	~2K tokens no matter how many tools you add
100+ Built-in Tools	Web search, databases, file ops, diagrams, conversions
Explicit Execution	See exactly what runs - `__ot brave.search(q="AI")`
MCP Server Proxy	Wrap existing MCP servers without the tool tax
Scaffold Tools	Build new tools as part of the conversation
Smart Tools	Delegate to cheaper LLMs (10脳 savings)
Single YAML Config	Global and project scopes, per-pack settings
Security Layers	AST validation, path boundaries, output sanitisation

Tools

15 packs, 100+ tools ready to use:

Pack	Tools	Description
`brave`	`search`, `news`	Web and news search
`code`	`search`, `search_batch`, `status`	Semantic code search
`context7`	`resolve`, `get_docs`	Library documentation
`convert`	`pdf_to_md`, `docx_to_md`, `pptx_to_md`	Document conversion
`db`	`query`, `schema`, `tables`	Database operations
`diagram`	`create`	Mermaid diagrams
`excel`	`read`, `write`, `query`	Excel files
`file`	`read`, `write`, `list`, `search`	File operations
`ground`	`search`	Google Grounding
`llm`	`transform`, `transform_file`	LLM-powered transforms
`ot`	`help`, `tools`, `stats`	Introspection
`package`	`npm`, `pypi`, `cargo`	Package versions
`ripgrep`	`search`, `count`	Fast code search
`scaffold`	`tool`	Generate new tools
`web`	`fetch`, `fetch_batch`	Web fetching

馃摉 Complete tools reference 鈥� full summary table with all 100+ tools

MCP Server Proxy

Wrap any existing MCP server and call it explicitly - without the tool tax:

# .onetool/onetool.yaml
mcp_servers:
  chrome-devtools:
    command: npx
    args: ["-y", "@anthropic-ai/chrome-devtools-mcp@latest"]
  github:
    command: npx
    args: ["-y", "@anthropic-ai/github-mcp-server@latest"]

__ot mcp.call(server="github", tool="get_file_contents", arguments={"path": "README.md"})

馃摉 Configuration guide

Extending

Drop a Python file, get a pack. No registration, no config:

# .onetool/tools/wiki.py
pack = "wiki"

def summary(*, title: str) -> str:
    """Get Wikipedia article summary."""
    import httpx
    url = f"https://en.wikipedia.org/api/rest_v1/page/summary/{title}"
    return httpx.get(url).json().get("extract", "Not found")

__ot wiki.summary(title="Python_(programming_language)")

馃摉 Creating tools guide

Documentation

Quickstart - 30 seconds to first tool call
Installation - All platforms
Configuration - YAML schema
Tools Reference - All 100+ tools
Security - Security layers
Extending - Build your own

References

Code Execution with MCP - Anthropic Engineering
Context Rot - Chroma Research

Contributing

Contribution guidelines

License

GPLv3 - Will transition to MIT at v2.0.

Support

If you find OneTool useful:

查看源码项目主页