OneTool MCP
概览
作者提供的说明(英文原文)
One MCP for devs incl Brave,Google,Tavily,Context7,AWS,Excalidraw,DB,GitHub,DevTools,Playwright
PopNx MCP 的三大支柱
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
- 用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
- 我们的基础检查i1 项中通过 1 项依据公开信息检查;尚未扫描代码
- 使用情况i非常新★ –
它能帮你做什么
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
- 连接方式: –
- 传输方式:
- 分类: 搜索与 AI 记忆
安装
选择你使用的 AI 应用,然后复制设置。
安装之前
- 基础检查:1 项中通过 1 项
- 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
- 注册中心没有列出需要填写的密钥。
作者没有在注册中心列出安装信息。请查看下方作者的 README。
它能做什么
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
基础检查i
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月9日
- ✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 beycom 验证,该账户拥有此仓库
- … 尚未检查
仍在维护
我们还没有从 GitHub 读取这个仓库
- … 尚未检查
有许可证
我们还没有从 GitHub 读取这个仓库
- – 不适用
端点有响应
它在你的电脑上运行,没有互联网端点
- – 不适用
使用 OAuth 登录
在你的电脑上运行,改用本地设置
- … 尚未检查
工具描述中没有隐藏指令
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与“搜索与 AI 记忆”中的其他服务器比较i
- 星标数多于此分类中其他 5754 个服务器的 0%
- 发布到注册中心的时间比此分类中其他 5754 个服务器的 8% 更新
- 基础检查结果等于或优于此分类中其他 5754 个服务器的 100%
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
常见问题
OneTool MCP 安全吗?
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
它需要哪些密钥或代码?
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在我的电脑上运行还是在云端?
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
它还在维护吗?
GitHub 仓库最后更新于–,最新版本(2.2.2)于7个月前进入注册中心。
哪些应用可以使用它?
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。
有什么可以替代它?
同一分类中有:Context7, Codebase Memory, Exa
替代选择
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Codebase Memory
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Exa
Connect AI agents to Exa for web search, content fetching, and multi-step research.
作者的 README
打开 README
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
🧿 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)
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):
curl -LsSf https://onetool.beycom.online/install.sh | sh # macOS / Linux
irm https://onetool.beycom.online/install.ps1 | iex # Windows (PowerShell)
Or install manually with uv:
uv tool install 'onetool-mcp[all]' # everything
onetool init --config ~/.onetool
Then print ready-to-paste MCP client config with resolved absolute paths and add it to your client (claude-code, claude-desktop, cursor, or vscode):
onetool init mcp-config --client claude-code # or omit --client for all four
That's it. All 250+ tools work out of the box.
Verify: onetool init validate --config ~/.onetool/onetool.yaml
Install the ot-ref skill into your agent with vercel-labs/skills - it teaches the call conventions and ships a greppable index of every tool signature:
npx skills add https://github.com/beycom/onetool-mcp --skill ot-ref --agent claude
What's Inside
| Search & docs | Brave, Google-grounded, and Tavily search (each with batch + answer modes), Context7 library docs, web fetch with extraction controls |
| Files & data | File ops with path boundaries, full Excel control, SQL databases, PDF/Word/PowerPoint → Markdown, ripgrep, package versions |
| Context economy | ctx handles for large outputs, partial file reads (toc/slice), image vision on a dedicated cheap model (zero host tokens), LLM delegation (10× savings) |
| Persistent state | mem memory with semantic + keyword search, history and rollback; knowledge RAG bases with AI enrichment; localhist Git-backed project snapshots |
| Visual | Live Excalidraw whiteboard with a Mermaid-compatible DSL and offline auto-layout, Mermaid/PlantUML/D2 diagrams, architecture models → draw.io-editable SVG |
| Runtime | MCP server proxy with runtime enable/disable/restart, direct CLI/API into the running process, ot-ref agent skill, in-conversation tool forging |
| Trust | age-encrypted secrets backed by your OS keychain, AST validation, path boundaries, output sanitisation, runtime stats with estimated savings |
Tools
28 packs, 253 tools ready to use (console in beta):
| Pack | Tools | Extra | Description |
|---|---|---|---|
arch | generate, validate, bundle_solution, … | [dev] | Architecture models → draw.io-editable SVG |
brave | search, news, image, video, search_batch | [util] | Brave web search |
chrome_util | highlight_element, guide_user, … | [dev] | Browser annotations (Chrome DevTools) |
console *(beta)* | show, display, list, read, clear | Messages to the upcoming onetool-console app | |
context7 | search, doc | [dev] | Library documentation |
convert | pdf, word, powerpoint, excel, auto | [util] | Documents → Markdown |
db | query, schema, tables, sample | [dev] | SQL databases |
diagram | render_diagram, batch_render, get_template, … | [dev] | Mermaid / PlantUML / D2 via Kroki |
excel | read, write, formula, create_table, … (24 tools) | [util] | Full Excel control |
file | read, write, edit, grep, slice, toc, … (16 tools) | [util] | File ops with path boundaries |
ground | search, dev, docs, reddit, search_batch | [util] | Google-grounded search with sources |
knowledge | search, ask, write, related, … (15 tools) | [util] | RAG knowledge bases (hybrid search) |
localhist | save, diff, restore, autosave_start, … (15 tools) | [dev] | Git-backed local history snapshots |
mem | write, search, ask, history, rollback, … (31 tools) | [util] | Persistent memory with semantic search |
ot | help, tools, stats, status, result, … (18 tools) | Introspection and management | |
ot_context (ctx) | write, read, grep, slice, toc, ask, … (13 tools) | Smart context store for large outputs | |
ot_forge | create_ext, validate_ext | Scaffold new tool packs | |
ot_image (img) | load, ask, clip_ask, summary, … (9 tools) | Image vision via a dedicated model | |
ot_llm | transform, transform_file | LLM-powered transforms | |
ot_secrets | set, encrypt, audit, rotate, … (8 tools) | Encrypted secrets management | |
ot_servers | enable, disable, restart, status | Runtime control of proxied servers | |
ot_timer | start, stop, elapsed, list, clear | Named timers | |
package | pypi, npm, version, audit, models | [dev] | Package versions and staleness |
play_util | highlight_element, guide_user, … | [dev] | Browser annotations (Playwright) |
ripgrep | search, count, files, types | [dev] | Fast code search |
tavily | search, research, extract, search_batch, … | [util] | AI-native search and extraction |
webfetch | fetch, fetch_batch | [dev] | Web content extraction |
whiteboard (wb) | open, draw, layout, screenshot, … (22 tools) | [util] | Live Excalidraw canvas |
📖 Complete tools reference — every signature, generated from source
MCP Server Proxy
Keep the MCP servers you already use. Wrap them in YAML and call them explicitly - as Python namespaces, without their tool tax:
# .onetool/onetool.yaml
servers: local_tools: type: stdio command: npx args: ["-y", "some-mcp-server@latest"] private_api: type: http url: ${PRIVATE_MCP_URL} auth: type: bearer token: ${PRIVATE_MCP_TOKEN}
__onetool private_api.read_resource(path="README.md")
Proxied servers can be enabled, disabled, and restarted mid-conversation with ot_servers - no client restart.
Secrets You Can Commit
onetool init walks you through encrypted secrets: values in secrets.yaml are age-encrypted, the private key lives in your OS keychain, and decryption happens transparently at load.
# secrets.yaml - safe to inspect, safe to commit
brave_api_key: age1enc:YWdlLWVuY3J5cHRpb24ub3JnL3YxCi0+IFgyNT...
Use from the CLI
Works as an MCP server and as a direct CLI bridge into the same running process - loaded config, secrets, and proxy connections stay warm. Useful for agent harnesses, scripts, and automation:
# Recommended local MCP root mode: stdio
onetool serve --config .onetool/onetool.yaml
URL-based MCP root mode for containerized clients
onetool serve --transport http --config .onetool/onetool.yaml --host 127.0.0.1 --port 8767 --path /mcp
Enable the MCP-owned direct API in onetool.yaml:
direct.host.enabled: true
Start OneTool as MCP, then use the port printed in startup logs.
onetool
只显示了开头部分;其余内容请在仓库中阅读