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Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

This server doesn't publish a one-line install command. Follow the setup in the source repository.

Summary

MCP server to query Cloud Champion's training catalog. Enables AI agents to search, filter, and get statistics about Microsoft partner resources like webinars, videos, learning paths, and podcasts.

README.md

CloudChampion MCP Server

Servidor MCP (Model Context Protocol) para consultar el catálogo de formación de Cloud Champion (cloudchampion.es y variantes por país).

Expone herramientas que permiten a agentes de IA buscar, filtrar y obtener estadísticas sobre webinars, vídeos, learning paths, podcasts y otros recursos de Microsoft para partners.

Arquitectura

Agente IA ──► MCP Server (FastMCP) ──► API Cloud Champion
                  │                     /wp-json/feed/content
                  │
                  └── Caché en memoria (TTL configurable)
  • Feed API: GET https://www.cloudchampion.es/wp-json/feed/content — catálogo global público (todos los países/idiomas)
  • Caché: En memoria con TTL de 10 min (configurable) para evitar llamadas excesivas
  • Búsqueda: Fuzzy matching sin tildes/diacríticos para español y otros idiomas
  • Transporte: Streamable HTTP (default), SSE o stdio

Herramientas disponibles (Tools)

| Tool | Descripción | |---|---| | buscar_formacion | Búsqueda textual + filtros combinables (país, idioma, tipo, audiencia, área, provider, fechas) | | listar_proximas_formaciones | Formaciones futuras en una ventana de N días | | detalle_formacion | Detalle completo de una formación por título parcial o ID | | listar_filtros_disponibles | Valores únicos disponibles para cada filtro (tipos, áreas, idiomas, etc.) | | estadisticas_catalogo | Estadísticas del catálogo: totales por tipo, área, audiencia, provider, rango de fechas |

Desarrollo local

Requisitos

  • Python 3.11+
  • pip

Instalación

# Clonar el repositorio
git clone <repo-url>
cd cloudchampion-mcp

# Instalar dependencias
pip install -r requirements.txt

# (Opcional) Copiar y ajustar variables de entorno
cp .env.example .env

Modo desarrollo con inspector web

fastmcp dev src/mcp_cloudchampion/server.py

Esto abre el inspector web de FastMCP donde puedes probar las tools interactivamente.

Modo stdio (para uso local con clientes MCP)

MCP_TRANSPORT=stdio python -m mcp_cloudchampion.server

Modo HTTP (para acceso remoto)

python -m mcp_cloudchampion.server
# Servidor en http://0.0.0.0:8000

Docker

Build

docker build -t mcp-cloudchampion .

Run

docker run -p 8000:8000 mcp-cloudchampion

Con variables de entorno custom

docker run -p 8000:8000 \
  -e CACHE_TTL_SECONDS=300 \
  -e LOG_LEVEL=DEBUG \
  mcp-cloudchampion

Despliegue en Azure Container Apps

La infraestructura se define como IaC con Bicep en la carpeta infra/.

1. Crear infraestructura con Bicep

RESOURCE_GROUP="rg-cloudchampion-mcp"
LOCATION="westeurope"

# Crear Resource Group
az group create --name $RESOURCE_GROUP --location $LOCATION

# Desplegar infraestructura (ACR + Log Analytics + Container Apps Env + Container App)
az deployment group create \
  --resource-group $RESOURCE_GROUP \
  --template-file infra/main.bicep \
  --parameters infra/main.parameters.json

# Ver outputs (FQDN, MCP endpoint, ACR login server)
az deployment group show \
  --resource-group $RESOURCE_GROUP \
  --name main \
  --query 'properties.outputs' -o json

Recursos creados:

  • Azure Container Registry (Basic SKU, admin habilitado)
  • Log Analytics Workspace (retención 30 días)
  • Container Apps Environment (con logging a Log Analytics)
  • Container App (scale to zero, 0.25 vCPU, 0.5 GiB RAM, ingress HTTP externo)

2. Build & Deploy de la imagen

ACR_NAME="acrcloudchampionmcp"
ACA_APP="mcp-cloudchampion"

# Build imagen en ACR
az acr build --registry $ACR_NAME --image mcp-cloudchampion:latest .

# Actualizar Container App con la nueva imagen
az containerapp update \
  --name $ACA_APP \
  --resource-group $RESOURCE_GROUP \
  --image "$ACR_NAME.azurecr.io/mcp-cloudchampion:latest"

3. Obtener URL

az containerapp show --name $ACA_APP --resource-group $RESOURCE_GROUP \
  --query "properties.configuration.ingress.fqdn" -o tsv

Personalizar parámetros

Edita infra/main.parameters.json para cambiar el nombre del ACR, CPU, memoria, réplicas, etc. Parámetros disponibles:

| Parámetro | Descripción | Default | |---|---|---| | acrName | Nombre del ACR (globalmente único) | acrcloudchampionmcp | | environmentName | Nombre del Container Apps Environment | env-cloudchampion-mcp | | appName | Nombre de la Container App | mcp-cloudchampion | | minReplicas | Mín. réplicas (0 = scale to zero) | 0 | | maxReplicas | Máx. réplicas | 3 | | cpu | CPU asignada | 0.25 | | memory | Memoria asignada | 0.5Gi | | cacheTtlSeconds | TTL de caché del feed | 600 | | logLevel | Nivel de logging | INFO |

CI/CD

El workflow de GitHub Actions (.github/workflows/deploy.yml) tiene dos jobs:

  1. infra — Despliega Bicep (solo si cambian ficheros en infra/ o se lanza manualmente con deploy_infra: true)
  2. build-and-deploy — Build de imagen en ACR + deploy a Container App (en cada push a main)

Requiere el secret AZURE_CREDENTIALS configurado en el repo.

Consumir el MCP

Desde VS Code / Claude Desktop

{
  "mcpServers": {
    "cloudchampion": {
      "url": "https://<tu-aca-url>.azurecontainerapps.io/mcp"
    }
  }
}

Desde un agente Python

from agents import Agent
from agents.mcp import MCPServerStreamableHttp

mcp = MCPServerStreamableHttp(url="https://<tu-aca-url>.azurecontainerapps.io/mcp")

agent = Agent(
    name="CloudChampionAssistant",
    instructions="Eres un asistente experto en formación de Cloud Champion...",
    mcp_servers=[mcp],
)

Variables de entorno

| Variable | Descripción | Default | |---|---|---| | CLOUDCHAMPION_FEED_URL | URL del feed de contenido | https://www.cloudchampion.es/wp-json/feed/content | | CACHE_TTL_SECONDS | TTL de la caché en segundos | 600 | | MCP_TRANSPORT | Transporte: streamable-http, sse, stdio | streamable-http | | MCP_HOST | Host de escucha | 0.0.0.0 | | MCP_PORT | Puerto de escucha | 8000 | | LOG_LEVEL | Nivel de logging | INFO |

Estructura del proyecto

├── src/
│   └── mcp_cloudchampion/
│       ├── __init__.py        # Versión del paquete
│       ├── __main__.py        # python -m entry point
│       ├── config.py          # Settings + logging setup
│       ├── text_utils.py      # Normalización de texto / fuzzy match
│       ├── feed_client.py     # Cliente HTTP + caché con TTL
│       ├── filters.py         # Motor de filtrado
│       └── server.py          # FastMCP server + 5 tools
├── Dockerfile                 # Multi-stage build
├── .dockerignore
├── .env.example
├── pyproject.toml
├── requirements.txt
├── README.md
└── .github/workflows/
    └── deploy.yml             # CI/CD → Azure Container Apps

Licencia

MIT

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