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

Amicus

作者:BourbonDog版本 4.14.3i★ –i在你的电脑上运行
注册名称io.github.BourbonDog/amicus

安装

概览

作者提供的说明(英文原文)

Multi-model LLM Council and parallel AI window for Claude Code. Fork any model, fold results back.

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: 搜索与 AI 记忆
  • 你需要填写:OPENROUTER_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: OPENROUTER_API_KEY, AMICUS_SKIP_POSTINSTALL

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": {
    "amicus": {
      "command": "npx",
      "args": [
        "-y",
        "amicus",
        "mcp"
      ],
      "env": {
        "OPENROUTER_API_KEY": "your-value",
        "AMICUS_SKIP_POSTINSTALL": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add amicus --env OPENROUTER_API_KEY=your-value --env AMICUS_SKIP_POSTINSTALL=your-value -- npx -y amicus 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": {
    "amicus": {
      "command": "npx",
      "args": [
        "-y",
        "amicus",
        "mcp"
      ],
      "env": {
        "OPENROUTER_API_KEY": "your-value",
        "AMICUS_SKIP_POSTINSTALL": "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": {
    "amicus": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "amicus",
        "mcp"
      ],
      "env": {
        "OPENROUTER_API_KEY": "your-value",
        "AMICUS_SKIP_POSTINSTALL": "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

  • OPENROUTER_API_KEY 机密 env
    OpenRouter API key (recommended multi-model route). Optional when a provider key is configured via 'amicus setup' (~/.config/amicus/.env) or OpenCode auth.json.
  • AMICUS_SKIP_POSTINSTALL env
    Set to 1 when a plugin/client manages registration itself (skips npm postinstall side effects).

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6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 BourbonDog 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 7248 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 7248 个服务器的 62% 更新
  • 基础检查结果等于或优于此分类中其他 7248 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

Amicus 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:OPENROUTER_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(4.14.3)于23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。

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:★ 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

Context7

作者:upstash

Up-to-date docs for AI agents

电脑或云端★ 64,224MIT今天更新
安装

Codebase Memory

作者:DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

在你的电脑上运行★ 48,148MIT20天前更新
安装

Exa

作者:exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

在云端运行★ 5,213MIT上个月更新
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。

Amicus

A multi-model LLM Council for Claude — with a parallel AI window underneath.

Hand Claude a plan, a design, a diff, an architecture decision, a manuscript — anything — and say *council review this*: Amicus routes it through several models from different families, has them anonymously cross-review each other, and a non-Claude chair synthesizes a verdict you turn into accept/deny edits. Or skip the ceremony and fork a single conversation to Gemini, GPT, DeepSeek, or any other model — it works in parallel with full context, and you fold the result back when you're ready. Claude orchestrates throughout; you stay in your editor.

The same council — more ways to run it: take it headless in CI with no Claude runtime, sharpen it with a debate round, or run it on free local models (Ollama, LM Studio, vLLM) at $0 — private and offline.

[Quick start ↓](#quick-start) · Commands · Documentation · Troubleshooting

Supported clients: Claude Code CLI, Claude Desktop, and Claude Cowork are fully tested and supported. Claude Code web is experimental.


Table of Contents

  • What is Amicus
  • The Council
  • Ways to run the council
  • Quick start
  • 1. Install
  • 2. Configure — don't skip this
  • 3. Your first council
  • 4. Your first sidecar
  • Requirements & Dependencies
  • The parallel window
  • Commands
  • Models
  • MCP integration
  • Configuration
  • JSON output
  • Windows
  • Troubleshooting
  • Documentation
  • Contributing
  • Built on OpenCode
  • Attribution & License

What is Amicus

One install delivers six things that work together:

  • The `second-opinion` LLM Council skill. Structured multi-model review: independent reviews → anonymized peer cross-review → a non-Claude chair verdict → tiered accept/deny decisions. This is the hero.
  • The `sidecar` chat skill. Ad-hoc fork/work/fold — spin up one other model in a real window (or headless), work alongside it, fold the summary back.
  • The `amicus` CLI (with an `am` alias) and an MCP server. The engine underneath both skills: launches sessions, shares context, runs parallel waves, and exposes the same surface to Claude as MCP tools.
  • A self-updating model catalog. Aliases and validation resolve against a live catalog fetched from provider APIs (cached locally), so model names stay current without a hard-coded table.
  • Observability. amicus watch renders any live or finished run (fan-out or council) from any terminal; --follow streams milestones as they happen; --on-complete fires a hook when a run lands; --retry-failed plus opt-in cheaper-model fallbacks recover dead legs without relaunching the whole wave; amicus spend answers "what did this cost, and where" with per-run attribution.
  • Council Workspace. amicus watch --ui: a window that shows a council *thinking* — live seats, the anonymized judge packet, the adjudication matrix, dissent drill-in, chair verdict, and cost-by-seat — for both live and historical runs. It also auto-opens on an MCP-invoked council run from Claude Code (local), so you no longer have to remember the flag (see docs/council.md).

Claude is the orchestrator. The council and chat skills run *on top of* the engine; you talk to Claude, and Claude drives Amicus.


The Council

Trigger it by saying *"council review this"* to Claude, or, on the plugin channel, run `/amicus:council` directly.

Why multi-model. Any single model — including the one running your session — has consistent blind spots. Route the *same* material through models from *different* families and the disagreements surface: missed issues, overstated confidence, claims one model alone would have waved through. The council is the structured version of that idea.

The flow, in five beats:

  1. Independent reviews. Each council model reviews the artifact on its own (one parallel wave), producing a structured findings list — claim, severity (blocker | major | minor | nit), location, rationale.
  2. Anonymized cross-review. Claude relabels every review (Review A, B, C…) and sends the identical bundle to every model. Each model ranks the reviews and adjudicates every finding (agree | dispute | neutral) — *unknowingly judging its own*, so self-bias washes out. This yields a street-cred ranking and sorts findings into Disputed / Confirmed / Contested / Singleton tiers. Self-bias is washed out per seat: if you deliberately seat one model twice, each seat's vote on the *other* seat's finding is counted as the real peer vote it is, and the finding is flagged when its only corroboration came from its own twin.
  3. Chair verdict. A designated non-Claude chair receives the de-anonymized picture — all reviews, rankings, and adjudications — and synthesizes an independent verdict. Claude presents it verbatim; Claude does not synthesize.
  4. Tiered decisions. Confirmed findings get one bulk accept/deny; Contested and Singleton findings are decided one at a time (accept / deny / modify).
  5. Outputs applied. Accepted findings are written into a reviewed copy of the source; the full run is captured in the run folder.
flowchart LR

A["Artifact"] --> B["Independent reviews"] B --> C["Anonymized cross-review"] C --> D["Chair verdict (non-Claude)"] D --> E["Tiered accept / deny"] E --> F["Reviewed copy

  • run folder"]

What a run produces (in output/ -council/):

  • review- .md × N — each model's independent review.
  • crossreview-matrix.md — the adjudication grid plus the de-anonymized street-cred table.
  • verdict.md — the chair's synthesis.
  • report.md — synthesis + the full decision log + a per-call run-stats table.
  • report.html — the deterministic renderer output (adjudication matrix, street-cred table, findings-by-tier, cost — no chair prose). This is the default artifact handed to the user.
  • For an editable source, the accepted edits land in -reviewed. next to the original.

Optional council elements (v2.2.0, all default off): four opt-in behaviors, offered once as a menu at launch — nothing turns on unless you name it, and the confirmation lists exactly what's on. Chair verdict scale *(standard since v2.2.0's follow-ups — no longer opt-in)*: the chair always closes with 3–5 hard questions and one parseable VERDICT: Ship it | Fix these first | Fundamental rethink line.

  • Critic seat — one reviewer swaps to a four-pass adversarial brief (adversarial pass, edge-case hunt, consistency check, executability test). Its findings enter the same anonymized bundle as everyone else's, so the bench disciplines the critic: manufactured negativity lands Disputed and dies in the tally.
  • Expert lenses — each reviewer takes a distinct expert perspective; you pick the panel domain (business, technical, customer, financial, or custom). Lens runs never feed the reliability ledger, and the report discloses the weakened cross-review anonymity.
  • Debate mode — after cross-review, every Contested or Disputed finding goes back to its raiser to defend, amend, or withdraw, and the disputing judges re-vote. Exactly one rebuttal round, then the final tally.
  • Claude in the council — Claude adds its own fresh review to the bundle so the bench ranks and adjudicates it. Claude is *judged* but never votes or chairs, so the verdict stays independent.

The critic and lens methodologies are adapted from the /critic and /debate agents in John Renaldi's product-kit (MIT); the briefing boilerplate lives in skills/second-opinion/SEAT-BRIEFS.md.

Cost is disclosed up front. Before any model launches, you see the run shape — including any enabled optional elements — for example:

This run uses 3 council models across 2 fanout waves + 1 chair call, with critic seat + debate mode ON (~7 base runs + up to 6 rebuttal calls).

Then the council waits for your confirmation.

The skill lives at [`skills/second-opinion/SKILL.md`](./skills/second-opinion/SKILL.md); the design spec behind it is [`skills/second-opinion/COUNCIL-DESIGN.md`](./skills/second-opinion/COUNCIL-DESIGN.md). For what amicus council tally|verdict|report|stats actually take as input and produce — field-by-field schemas, verdict.json's provenance, and a full worked example run against the real CLI — see [docs/council.md](./docs/council.md).


Ways to run the council

The council is the hero — start with the everyday way, and reach for the more powerful ways when you need them:

  • Just ask, in Claude Code. Hand Claude a plan, diff, design, or manuscript and say *"council review this."* The second-opinion skill runs the whole ritual above in your session, with no setup beyond your API keys. This is how most people use it. → Quick start
  • Headless, in CI, with no Claude runtime. amicus council run --prompt-file plan.md --council free runs that same pipeline in one command — reviews → cross-review → tally → chair verdict — writing verdict.json and report.html. It needs no Claude session, so it drops straight into CI. → Headless council (CI)
  • With a debate round. Add --debate and every Contested or Disputed finding goes back to its raiser to defend, amend, or withdraw while the disputing judges re-vote — exactly one rebuttal round, then the final tally. → The Council
  • On free, local, private models — at $0. Point the council (and sidecars) at an OpenAI-compatible server already running on your machine — Ollama, LM Studio, or vLLM — with amicus provider add. No API key, no per-token bill, nothing leaves your machine, and it works

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