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

Plzebo

作者:wkoverfield版本 0.2.0i★ –i在你的电脑上运行
注册名称io.github.wkoverfield/plzebo

安装

概览

作者提供的说明(英文原文)

Cost-parity bench for agent loops: $/success and time across model mixes, with verifiable receipts.

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: 其他
  • 你需要填写:ANTHROPIC_API_KEY, OPENAI_API_KEY

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)。
  • 需要你自己填写: ANTHROPIC_API_KEY, OPENAI_API_KEY

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": {
    "plzebo": {
      "command": "npx",
      "args": [
        "-y",
        "plzebo"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "your-value",
        "OPENAI_API_KEY": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add plzebo --env ANTHROPIC_API_KEY=your-value --env OPENAI_API_KEY=your-value -- npx -y plzebo

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": {
    "plzebo": {
      "command": "npx",
      "args": [
        "-y",
        "plzebo"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "your-value",
        "OPENAI_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": {
    "plzebo": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "plzebo"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "your-value",
        "OPENAI_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

  • ANTHROPIC_API_KEY 机密 env
    Real Anthropic key for placebo-mode arms; arms only ever see placebo keys. Optional when every arm uses passthrough auth.
  • OPENAI_API_KEY 机密 env
    Real OpenAI-compatible key for placebo-mode arms. Optional when every arm uses passthrough auth.

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 wkoverfield 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“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 18349 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 18349 个服务器的 21% 更新
  • 基础检查结果等于或优于此分类中其他 18349 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

Plzebo 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:ANTHROPIC_API_KEY, OPENAI_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(0.2.0)于3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。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, arr-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

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211前天更新
安装

arr-mcp

作者:bardesss

One server, 40 tools, the whole media stack: *arrs, Jellyfin, Plex, Seerr, Cleanuparr, downloaders

在你的电脑上运行今天更新
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。

plzebo

Cost-parity bench for agent loops. Point it at two or more ways of getting the same task done (a cheaper model mix, a different setup, a tool on vs off) and it measures which one delivers the outcome for less, in dollars and in minutes, and whether the gap is real or noise. Runs locally, on your own keys or your own subscription. An agent can call it on itself over MCP.

The headline metric is cost per successful outcome: total metered spend divided by successes, compared across arms with a 95% confidence interval. Time per successful outcome is reported beside it. When the data cannot support a claim, plzebo says so instead of making it.

How it measures

  • Arms are whole loops. An arm is a shell command that runs an agent to completion on a task, plus model rewrite rules applied at a local metering gateway. Loop code can be byte-identical across arms while the gateway maps every claude-* call to each arm's model.
  • Every model call transits the gateway. Arms receive a placebo key (sk-placebo-...) and a redirected base URL; the gateway swaps in the real key upstream and records provider-reported token usage per call. A call that bypasses the gateway fails at the provider instead of billing invisibly, and a trial with zero metered calls is flagged, never compared.
  • Trials are paired and interleaved. K pairs run back to back with a seeded coin flip deciding arm order per pair, so provider drift lands inside pairs. Prompt caching is disabled and every trial carries a unique nonce, so no arm warms a cache for another.
  • Grading never trusts the agent's tree. The diff is filtered against a protected-path list (tests, runner config), applied to a pristine checkout, and the test command runs there. Editing the tests fails the trial.
  • Statistics refuse to overclaim. Success differences use an exact McNemar test with Holm correction across arms. Parity requires an equivalence test, not just a failed significance test. Cost and time deltas come from a paired bootstrap. Fewer than five successes on either side blocks cost rulings. Timeouts are graded failures with spend included; crashes and provider throttling (429/529) are excluded with spend disclosed. Every refusal is printed as an explicit do-not-claim line.
  • Receipts are the artifact. Every run writes a JSON receipt: the spec and its pre-registration hash, every trial's raw rows (tokens, per-call status, changed paths, output tails), the stats inputs, the pricing table version, and a generated estimand statement. plzebo verify receipt.json recomputes every derived number from the raw rows and reports any divergence.

Requirements

Node 22.6 or later (the CLI runs its TypeScript sources through Node type stripping; the launcher supplies the flag on versions that need it). Git, plus whatever your arms and oracle need (for the examples here: python3).

Quick start

npx plzebo run spec.yaml --estimate   # prices the run from prior receipts; spends nothing

npx plzebo run spec.yaml # runs the experiment npx plzebo verify # recompute a receipt's claims from its raw rows

A spec:

name: sonnet-vs-opus

fixture: repo: ./my-fixture-repo # a git repo; every trial gets a fresh clone ref: main task: "Make the failing tests in this repo pass. Do not edit the tests." arms: sonnet: cmd: claude --print "$PLZEBO_TASK" --dangerously-skip-permissions --strict-mcp-config --mcp-config '{"mcpServers":{}}' --model claude-sonnet-5 auth: passthrough # runs on your logged-in Claude subscription rewrite: claude-*: claude-sonnet-5 # pin every call this arm makes, including auxiliary ones opus: cmd: claude --print "$PLZEBO_TASK" --dangerously-skip-permissions --strict-mcp-config --mcp-config '{"mcpServers":{}}' --model claude-opus-4-7 auth: passthrough rewrite: claude-*: claude-opus-4-7 baseline: opus oracle: cmd: [python3, -m, unittest, discover, -s, tests, -t, .] k: 3 trialTimeoutMs: 600000 budgetUsd: 30 # hard kill switch enforced at the gateway

Every run prints its cost estimate before the first trial. A run without a budget is refused. Start with a small K: the report on an inconclusive run prints the exact K that would resolve it and the estimated cost, and plzebo extend --to-k K reuses the trials you already paid for. A receipt can be extended once, and the extension is disclosed inside it.

Auth modes

  • auth: placebo (default): you export ANTHROPIC_API_KEY or OPENAI_API_KEY; arms only ever see placebo keys. Strongest metering guarantee: a bypassing call fails loudly.
  • auth: passthrough: the arm uses its own login. No API credits are spent; USD is imputed from metered tokens at list rates and the receipt discloses this. Tokens are the ground truth either way. Verified for Claude Code, which honors ANTHROPIC_BASE_URL under subscription auth. Codex under ChatGPT auth routes to its own backend and ignores OPENAI_BASE_URL, so subscription-authed Codex is unmeterable; run Codex arms in API-key mode via the codex-cli template instead.

Two caveats for passthrough arms. A trial that bypasses the meter is excluded rather than falsely counted, but the tokens it consumed upstream are real; the receipt cannot see them. And a personal login carries personal agent configuration: instructions, hooks, and memory files travel with it, which can inflate costs and, for agents that act on standing instructions, cause writes outside the trial workspace. Prefer isolated-config templates when comparing loops rather than your own setup.

Model-mix arms (orchestrator and workers on different models)

Every cost node in a receipt records two models: role, the model the loop REQUESTED, and model, what the arm's rewrite rules resolved it to. A loop that requests different models for different jobs (a main session on one model, subagents on another) therefore encodes its role structure into the receipt, and arms that share the same command can bind those roles differently through rewrites alone:

arms:

mixed: cmd: sh scripts/arms/subagent-mix.sh # opus main session + a worker agent definition requesting sonnet auth: passthrough rewrite: claude-opus-*: claude-opus-4-7 # orchestrator stays opus claude-sonnet-*: claude-sonnet-5 # workers stay sonnet claude-*: claude-opus-4-7 # catch-all LAST: wildcard rules match in order after exact keys all_opus: cmd: sh scripts/arms/subagent-mix.sh # byte-identical loop; only the mapping differs auth: passthrough rewrite: claude-*: claude-opus-4-7

The packaged scripts/arms/subagent-mix.sh shows the Claude Code shape: a headless session with an inline --agents definition whose worker requests a different model than the main session. Adapt the agent prompt and models to your task.

A model-mix comparison is only valid when the loop actually delegated: a trial whose cost tree has no worker-role calls measured a solo run, not a mix.

npx plzebo fidelity <receipt.json|run-dir>        # per-trial requested -> resolved counts

npx plzebo fidelity --worker "claude-haiku-*"

fidelity exits 1 if any completed trial never made a worker-role call, and prints each trial's call counts, tokens, and imputed spend grouped by requested and resolved model, so the mix an arm claims is checkable from its receipt.

Providers

The gateway speaks two wire formats: Anthropic and OpenAI-compatible, which covers most open-weight serving (Ollama, vLLM, OpenRouter, Together, and similar). Arms can override providers individually:

arms:

local-qwen: cmd: my-loop --task "$PLZEBO_TASK" upstreams: openai: http://127.0.0.1:11434 # any OpenAI-compatible server gpt: cmd: my-loop --task "$PLZEBO_TASK" keysFrom: openai: OPENAI_API_KEY # env var NAME; specs never contain key values

Constraint: plzebo can only meter loops that authenticate with a key or token and honor a redirectable base URL (ANTHROPIC_BASE_URL / OPENAI_BASE_URL).

MCP

npx plzebo-mcp serves four tools on stdio: measure_start, measure_extend, measure_status, and measure_result. Starting a measurement is two-phase: the first call validates the request and returns a cost estimate plus a one-time confirm token while spending nothing; only a second call presenting that token runs trials. A budget is mandatory, and MCP arms come only from named templates (claude-cli, claude-subscription, codex-cli), never raw shell. Job state and receipts persist under .plzebo/, so verdicts survive the session that produced them.

What a receipt supports, and what it does not

A receipt is a single-task result under a stated model mapping. It is not a model capability ranking and does not generalize beyond its fixture; the estimand text inside the receipt says exactly this. USD figures on passthrough arms are imputed at pricing-table rates from metered tokens, not billed spend, and the pricing table version travels in the receipt so the numbers stay recomputable after prices change.

License

MIT

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