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Amicus

de BourbonDogversión 4.14.3i★ –iSe ejecuta en tu computadora
Nombre en el registroio.github.BourbonDog/amicus

Instalar

Resumen

Descripción del creador (original en inglés)

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

Los tres pilares de PopNx MCP

Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.

Qué puedes hacer con él

Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.

  • Conexión: Se ejecuta en tu computadora
  • Transporte: stdio
  • Categoría: Búsqueda y memoria de IA
  • Debes completar: OPENROUTER_API_KEY

Instalación

Elige la app de IA que usas y copia la configuración.

Antes de instalar

  • Revisiones básicas: 1 de 1 superadas
  • Se ejecuta en tu computadora con los permisos de tu usuario (archivos, red, apps).
  • Debes completar tú: OPENROUTER_API_KEY, AMICUS_SKIP_POSTINSTALL

Los valores marcados como secretos son llaves de tu cuenta. Nunca los compartas ni los pegues en un chat.

Necesitas

  • npmNode.js instalado (para el comando npx)

¿Qué app usas?

Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.

Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json

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

Ejecuta esto en tu terminal

claude mcp add amicus --env OPENROUTER_API_KEY=your-value --env AMICUS_SKIP_POSTINSTALL=your-value -- npx -y amicus mcp

Completa los valores vacíos antes de ejecutarlo.

Abrir en Cursor

O copia la configuración tú

Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json

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

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Abrir en VS Code

O copia la configuración tú

Pégalo en .vscode/mcp.json de tu proyecto

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

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.

Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.

Valores que debes completar

  • OPENROUTER_API_KEY secreto 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).

Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.

Qué puede hacer

Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.

Revisiones básicasi

Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026

  • ✓ Superada

    El creador coincide con el repo

    El nombre en el registro se verificó con la cuenta de GitHub BourbonDog, dueña del repo

  • … Aún sin revisar

    Sigue en mantenimiento

    Todavía no hemos leído este repo en GitHub

  • … Aún sin revisar

    Tiene licencia

    Todavía no hemos leído este repo en GitHub

  • – No aplica

    El endpoint responde

    Este se ejecuta en tu computadora; no hay endpoint en internet

  • – No aplica

    Inicio de sesión con OAuth

    Se ejecuta en tu computadora y usa ajustes locales en su lugar

  • … Aún sin revisar

    Sin instrucciones ocultas en las descripciones de herramientas

    Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet

Comparado con otros en Búsqueda y memoria de IAi

  • Más estrellas que el 0% de los otros 7254 servidores de esta categoría
  • Publicado en el registro más recientemente que el 62% de los otros 7254 servidores de esta categoría
  • Revisiones básicas iguales o mejores que el 100% de los otros 7254 servidores de esta categoría

Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.

Preguntas frecuentes

¿Es seguro Amicus?

Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.

¿Qué claves o códigos necesita?

Debes completar: OPENROUTER_API_KEY

¿Se ejecuta en mi computadora o en la nube?

Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).

¿Sigue en mantenimiento?

El repo de GitHub cambió por última vez –, y la última versión (4.14.3) llegó al registro hace 23 días.

¿Qué apps pueden usarlo?

Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.

¿Qué puedo usar en su lugar?

En la misma categoría: Context7, Codebase Memory, Exa

Alternativas

Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.

Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi

Context7

de upstash

Up-to-date docs for AI agents

Computadora o nube★ 64.224MITActualizado hoy
Instalar

Codebase Memory

de DeusData

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

Se ejecuta en tu computadora★ 48.148MITActualizado hace 20 días
Instalar

Exa

de exa-labs

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

Se ejecuta en la nube★ 5213MITActualizado el mes pasado
Instalar

README del creador

Abrir el README

Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.

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

Solo se muestra el principio; lee el resto en el repo

Pregunta a PopNx