原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Kitsune MCP

作者:kaiser-data版本 0.22.7i★ –i在你的电脑上运行
注册名称io.github.kaiser-data/kitsune-mcp

安装

概览

作者提供的说明(英文原文)

Hot-reload for MCP servers + mount any community server mid-session, Docker optional. No restarts.

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。

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: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 开发者工具
  • 你需要填写:SMITHERY_API_KEY

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "kitsune": {
      "command": "npx",
      "args": [
        "-y",
        "kitsune-mcp"
      ],
      "env": {
        "SMITHERY_API_KEY": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add kitsune --env SMITHERY_API_KEY=your-value -- npx -y kitsune-mcp

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "kitsune": {
      "command": "npx",
      "args": [
        "-y",
        "kitsune-mcp"
      ],
      "env": {
        "SMITHERY_API_KEY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "kitsune": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "kitsune-mcp"
      ],
      "env": {
        "SMITHERY_API_KEY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • SMITHERY_API_KEY 机密 env
    Smithery API key for accessing 3,000+ verified MCP servers. Get yours at smithery.ai/account/api-keys

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

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7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 kaiser-data 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“开发者工具”中的其他服务器比较i

  • 星标数多于此分类中其他 1394 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 1394 个服务器的 86% 更新
  • 基础检查结果等于或优于此分类中其他 1394 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

Kitsune 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?

你需要填写:SMITHERY_API_KEY

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(0.22.7)于6天前进入注册中心。

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。你的电脑上还需要有 Node.js, Python (uv)。

有什么可以替代它?

同一分类中有:GitHub, Desktop Commander, Cloudflare MCP

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:★ 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

GitHub

作者:github

Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.

电脑或云端★ 34,245MIT3天前更新
安装

Desktop Commander

作者:wonderwhy-er

MCP server for terminal commands, file operations, and process management

在你的电脑上运行★ 10,225MIT16天前更新
安装

Cloudflare MCP

作者:cloudflare

Cloudflare MCP servers

在云端运行★ 4,446Apache-2.014个月前更新
安装

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。

🦊 Kitsune MCP Let your agent test the MCP server it's building.

Edit a tool, reload("dev") , call it again. No client restart. ⭐ Saved you a restart? Star it on GitHub so others find it. 📖 Documentation · Hot-reload tutorial · Tools reference

AI agents installing this server (Cline, Claude Code, Cursor, …): follow llms-install.md. No clone or build needed. Add the uvx kitsune-mcp entry to your MCP settings.

One prompt: Claude finds the bug, fixes it, reloads, checks again. Real recording, 31 s.


Why

Your agent edits an MCP tool, but the client still runs the old process. Someone has to restart it before the agent can test the fix.

With Kitsune, connect, call and reload are tools. The agent runs the whole loop itself:

connect("uv run my-mcp-server", name="dev")  # start your server

shapeshift("dev") # its tools appear in the client call("summarize", arguments={"url": "https://example.com"})

… the agent (or you) edits the tool …

reload("dev") # restart on fresh code, remount call("summarize", arguments={"url": "https://example.com"}) # new code, same session

No Docker needed: connect() runs your own server as a plain local process, so the loop stays fast.

It also mounts any of 130,000+ servers from 7 registries mid-session. If Docker is installed, community packages run caged.

Try it: hot-reload tutorial · examples/demo-hot-reload/

Install

Claude Code

claude mcp add -s user kitsune -- uvx kitsune-mcp

Any other client (Claude Desktop, Cursor, Windsurf, Cline, Zed, …):

{

"mcpServers": { "kitsune": { "command": "uvx", "args": ["kitsune-mcp"] } } }

Also on PyPI (pip install kitsune-mcp, then "command": "kitsune-mcp") and npm (npx kitsune-mcp, delegates to uvx).

Requirements: Python 3.12+ · uv · node/npx for npm-based servers · Docker optional: not used for hot-reload, only to cage community servers when installed.

Three things it does

LoopWhat you get
MCP REPLconnect → shapeshift → edit → reload → callIterate on your own server without restarting the client
Long-tail reachsearch → shapeshift → call → shapeshift()Use a server once without adding it to your config forever
Try before you trustconfirm=True + Docker cage + version pinsRun community npm/PyPI code contained, not as your user
Borrow a server you never configured
search("web scraping")

shapeshift("firecrawl", tools=["scrape_url"]) # mount one tool, not the whole server call("scrape_url", arguments={"url": "https://example.com"}) shapeshift() # drop it, session stays up

Try a community package, caged
search("pdf", registry="glama")

shapeshift("mcp-pdf-tools", confirm=True) # npm/PyPI run in hardened Docker when available call("extract_text", arguments={"path": "report.pdf"}) shapeshift()

Add credentials mid-session
auth("BRAVE_API_KEY", "sk-...")  # saved to ~/.kitsune/.env, no restart

shapeshift("brave", tools=["brave_web_search"])

Full live walkthrough: docs/demo-realtime.md.

When to use it, when not to

Use Kitsune when…Skip it when…
You're building an MCP server and want an edit/reload loopYou only use 1–3 trusted servers (configure them natively)
A task needs a server that isn't in your configEvery turn hits the same server (keep it always-on)
You want to evaluate community MCP code without installing it for goodYou want lower token use: the base cost is ~1,774 tokens/turn, and modern clients already defer tool schemas
Your MCP config is crowded (GATEWAY)You need a sub-second first call (cold mount takes ~1–15 s)

How it works

shapeshift(server_id) picks a transport (stdio, HTTP+SSE, WebSocket, Docker), connects, reads tools/list, and registers each tool as a native tool with the server's real schema. The client receives notifications/tools/list_changed and sees first-class tools, with no wrapper in between. shapeshift() with no argument removes them and closes the connection.

search() covers the official servers repo, the MCP Registry, Glama, npm, PyPI, GitHub (github:owner/repo) and Smithery (hosted servers, free API key).

Tools

Default profile: 9 tools, ~1,774 tokens/turn (measured with python examples/benchmark.py).

ToolRole
connect(command, name)Start a persistent local server, e.g. the one you're developing
reload(name)Release, restart on fresh code, remount, in one call
release(name)Stop a persistent server
search(query, registry?)Search 7 registries
shapeshift(server_id?, tools=[…])Mount a server's tools (all or a subset); no argument drops them
call(tool_name, arguments)Call a tool; the server is inferred when mounted
auth(var_or_server, value?)Set an env key or run an OAuth 2.1 browser flow
auto(task, server_hint=)Search, mount and call in one step
status()Current form, connection pool, session stats

KITSUNE_TOOLS=all (or the kitsune-forge command) adds developer tools: inspect (schemas, credential check, token cost), test (quality score 0–100), bench (p50/p95 latency), compare, prewarm, craft, setup, and more. See docs/tools.md. Companion skills for Claude Code: kitsune-dev, kitsune-improve.

Safety, in short

  • Community sources need consent. npm, PyPI and GitHub servers require confirm=True. The model can set that flag itself, so real approval belongs in your client's tool-approval UI.
  • `connect()` runs the command it is given, as your user, with no consent gate and no cage. It is meant for your own code. Approve connect calls in your client before the agent runs them.
  • Community packages run in a Docker cage by default when Docker is installed: no host filesystem, --cap-drop ALL, read-only root, memory and PID limits. Credentials are passed by name, never in argv.
  • Version pins (TOFU). A later malicious publish doesn't silently replace a version you already ran.
  • Opt-in action guard. A ~/.kitsune/policy.json checks every downstream call against allow/ask/deny rules, path roots and a host allowlist. ask goes to you through MCP elicitation.
  • Install commands are validated and launched without a shell. fetch() blocks private hosts and re-checks every redirect.

Don't run it unattended with production admin, billing or security credentials. The full model, including what it does not protect against: docs/safety.md.

More

  • Configuration: env and .env lookup, tool profiles, sandbox and trust settings, Smithery, GATEWAY, mount patterns
  • Performance: cold/warm latency and token cost compared with always-on servers
  • Transports · Compatibility · Agent patterns · Worked scenarios

Why "Kitsune"?

In Japanese folklore the kitsune (狐) is known for what it can *become*: it borrows a form, uses that power, casts it off and returns to itself. That is the product loop.

*I am not Japanese, and I use this name with the highest respect for the mythology and culture it comes from. The parallel felt too precise to ignore.*

Contributing

make dev     # install with dev dependencies

make test # pytest make lint # ruff

Issues and PRs welcome: github.com/kaiser-data/kitsune-mcp · CHANGELOG.md


*MIT License · Python 3.12+ · Built on FastMCP*

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