MORAGENT -- AI Agent Studio

Design, learn, and deploy agentic AI projects in Claude Code.

You: /moragent
Claude: 9-option guided menu -> create project, agents, skills, learn, quality check...

What is MORAGENT?

MORAGENT is an MCP plugin for Claude Code that turns it into a full AI Agent Studio. It provides 11 tools and a guided menu (/moragent) that helps you structure, create, and operate multi-agent projects -- without writing any code.

It works by scanning your workspace, understanding what agents and skills you already have, and recommending what to create next. Think of it as an opinionated framework that enforces good practices: reuse over duplication, quality gates before delivery, and teaching through analogies.

Who is it for?

You don't need to code. Just install Claude Code, type /moragent, and follow the menu.

Quick Start

Requirements

• Claude Code installed

• Python 3.10+

Get started (macOS / Linux)

git clone https://github.com/EduardoMoraga/moragent.git
cd moragent
python3 -m pip install "mcp[cli]"
claude

Claude Code auto-detects the MCP server and the /moragent skill. Type /moragent and you're in. No path editing required — .mcp.json runs python3 server.py from the project root.

Get started (Windows)

Same steps, but on Windows the Python launcher is usually python (not python3). Tell the MCP server which interpreter to use by setting PYTHON_CMD once, then launch:

git clone https://github.com/EduardoMoraga/moragent.git
cd moragent
python -m pip install "mcp[cli]"
setx PYTHON_CMD python   # one-time; open a NEW terminal afterward
claude

.mcp.json resolves the interpreter as ${PYTHON_CMD:-python3} — it defaults to python3 (macOS/Linux) and falls back to whatever you set in PYTHON_CMD (e.g. python on Windows).

Install in an existing project

cd my-project
python /path/to/moragent/install.py
claude

The installer copies server.py, creates .mcp.json, and registers /moragent in your project.

Tools (11 MCP tools)

Menu (/moragent)

MORAGENT AI Agent Studio
========================

  1. New project        -- Describe your idea, get full structure
  2. Create agent       -- Specialized agent with role and memory
  3. Create skill       -- Reusable procedure (/name)
  4. My infrastructure  -- Dashboard of agents, skills, memories
  5. Learn              -- Agentic AI concepts with analogies
  6. Quality check      -- Checklist before delivering
  7. Find references    -- Previous work as starting point
  8. Onboarding         -- How everything works (folders, files, flow)
  9. Enrich             -- Improve an existing agent or skill

Architecture

You type something
       |
       v
  CLAUDE.md (orchestrator)
  Decides which agents to use
       |
       v
  Agent activates:
    1. Reads CLAUDE.md (global context)
    2. Reads its identity (.claude/agents/*.md)
    3. Reads its memory (.claude/agent-memory/)
    4. Executes and returns result
       |
       v
  You receive consolidated output

Workspace structure

my-project/
  CLAUDE.md                    <-- Orchestrator (project brain)
  .claude/
    agents/
      data-analyst.md          <-- Agent identity
      report-writer.md
    skills/
      etl-run.md               <-- Reusable procedure
      client-status.md
    agent-memory/
      data-analyst/
        MEMORY.md              <-- Persistent memory
  .mcp.json                    <-- MCP server config

Key Concepts

Orchestration Protocol

MORAGENT injects an orchestration protocol into every Claude Code session:

1. Before starting a project -- call moragent_advisor to scan infra and recommend architecture

2. Before delivering output -- call moragent_quality_check to verify quality

3. Before starting from scratch -- call moragent_find_references to find prior work

4. After scaffolding -- call moragent_enrich on each agent to ensure quality

5. When creating agents -- reuse existing ones first; 3 focused agents > 10 generic ones

Real-World Example

In a single 45-minute session using MORAGENT:

• 3 specialized agents created (researcher, writer, data engineer)

• 6 reusable skills defined

• 1 research brief with 10 verified papers

• 1 LinkedIn post (1,050 words) ready to publish

• 1 weekly editorial calendar

All orchestrated with Agent Teams, zero fabricated data, real sources with URLs.

FAQ

Q: Does MORAGENT send my data anywhere? A: No. It runs 100% locally as a Python MCP server. It only reads/writes files in your project directory. No API calls, no telemetry, no external connections.

Q: Can I use it with models other than Claude? A: Not currently. MORAGENT is built specifically for Claude Code's MCP protocol.

Q: What if I already have agents and skills? A: MORAGENT scans your existing infrastructure first and recommends reusing what you have before creating anything new.

Q: How do I update? A: cd moragent && git pull -- then restart Claude Code.

Q: Can I contribute? A: Yes! See CONTRIBUTING.md.

Documentacion en Espanol

Que es MORAGENT?

MORAGENT es un plugin MCP para Claude Code que lo convierte en un AI Agent Studio completo. Proporciona 11 herramientas y un menu guiado (/moragent) que te ayuda a estructurar, crear y operar proyectos multi-agente -- sin escribir codigo.

Para quien es

• Principiantes: Aprende que es un agente, una skill, un CLAUDE.md -- con analogias simples.

• Intermedios: Crea proyectos completos con agentes y skills en minutos.

• Avanzados: Quality gates, busqueda de referencias, orquestacion multi-agente.

No necesitas saber programar. Solo necesitas Claude Code y escribir /moragent.

Instalacion (macOS / Linux)

git clone https://github.com/EduardoMoraga/moragent.git
cd moragent
python3 -m pip install "mcp[cli]"
claude

Claude Code detecta automaticamente el servidor MCP y el skill /moragent. Solo escribe /moragent y listo. No hay que editar rutas: .mcp.json corre python3 server.py desde la raiz del proyecto.

Instalacion (Windows)

Los mismos pasos, pero en Windows el interprete suele ser python (no python3). Indicaselo al servidor MCP con PYTHON_CMD una sola vez:

git clone https://github.com/EduardoMoraga/moragent.git
cd moragent
python -m pip install "mcp[cli]"
setx PYTHON_CMD python   # una vez; abre una terminal NUEVA despues
claude

.mcp.json resuelve el interprete como ${PYTHON_CMD:-python3}: por defecto usa python3 (macOS/Linux) y respeta lo que definas en PYTHON_CMD (ej. python en Windows).

Instalar en un proyecto existente

cd mi-proyecto
python /ruta/a/moragent/install.py
claude

Conceptos clave

Menu (/moragent)

  1. Nuevo proyecto     -- Describe tu idea y te armo todo
  2. Crear agente       -- Agente con rol, modelo y memoria
  3. Crear skill        -- Procedimiento reutilizable (/nombre)
  4. Mi infraestructura -- Dashboard completo
  5. Aprender           -- Conceptos con analogias y diagramas
  6. Verificar calidad  -- Checklist antes de entregar
  7. Buscar referencias -- Trabajo previo como base
  8. Onboarding         -- Como funciona todo
  9. Enriquecer         -- Mejorar un agente o skill existente

Ejemplo real

En una sesion de 45 minutos, usando MORAGENT se construyo:

• 3 agentes especializados (investigador, redactor, ingeniero de datos)

• 6 skills reutilizables

• 1 research brief con 10 papers verificados

• 1 post LinkedIn de 1.050 palabras listo para publicar

• 1 calendario editorial semanal

Todo orquestado con Teams, cero datos inventados, fuentes reales con URL.

License

MIT -- Eduardo Moraga, 2026

Contributing

See CONTRIBUTING.md for guidelines.