AEM Assets MCP Server

AEM Assets MCP Server

A Model Context Protocol (MCP) server for Adobe Experience Manager (AEM) Assets Author API built with Python and FastAPI. Can be deployed to Vercel (Phase 1) or Google Cloud Run (Phase 2) and used with ChatGPT.

🚀 Features

This MCP server provides tools to interact with AEM Assets:

• List folders - Browse folders in your AEM Assets repository
• List published assets - Find all assets that have been published
• Search assets - Search for assets by keywords (e.g., "Electric Vehicle")
• List assets by folder - Get all assets within a specific folder
• Bulk update metadata - Update metadata for all assets in a folder
• List assets by creator - Find assets uploaded by a specific user
• Get asset details - Retrieve detailed information about a specific asset

📋 Prerequisites

General Requirements

1. Adobe Experience Manager Assets Author API Access

   • AEM base URL
   • OAuth Server-to-Server credentials:
     • Client ID (API Key)
     • Client Secret
     • Scopes
   • See GET_CREDENTIALS.md for how to obtain these

2. Python 3.11+

Phase 1 Requirements (Vercel)

• Vercel account
• ChatGPT Plus/Pro (to use MCP servers)

Phase 2 Requirements (Google Cloud Run)

• Google Cloud Platform account
• gcloud CLI installed
• Terraform installed (for infrastructure as code)
• Docker installed
• GitHub account (for CI/CD)

🛠️ Tech Stack

• Python 3.11 - Core language
• FastAPI - Modern async web framework
• HTTPX - Async HTTP client
• Pydantic - Data validation
• OAuth Server-to-Server - Automatic token refresh
• Docker - Containerization
• Terraform - Infrastructure as Code
• GitHub Actions - CI/CD

📁 Project Structure

.
├── app/
│   ├── __init__.py           # Package initialization
│   ├── main.py               # FastAPI application
│   ├── aem_client.py         # AEM Assets API client
│   └── models.py             # Pydantic models
├── terraform/
│   ├── main.tf               # Main Terraform configuration
│   ├── variables.tf          # Terraform variables
│   └── terraform.tfvars.example
├── .github/workflows/
│   ├── deploy-cloud-run.yml  # Cloud Run deployment
│   ├── terraform-apply.yml   # Terraform workflow
│   └── test.yml              # Testing workflow
├── Dockerfile                # Docker configuration
├── requirements.txt          # Python dependencies
├── vercel.json              # Vercel configuration
├── env.example              # Environment template
└── README.md

🚀 Quick Start

Local Development

1. Clone the repository:

cd "SC Practice 20260130 - Assets MCP"

2. Create virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

4. Configure environment:

# Option 1: Interactive setup (recommended)
./create-env.sh

# Option 2: Manual setup
cp env.example .env
nano .env  # Edit with your AEM credentials

See GET_CREDENTIALS.md for how to get your OAuth credentials.

5. Run locally:

uvicorn app.main:app --reload

Visit http://localhost:8000 to see the server info.

Docker Development

# Build image
docker build -t aem-mcp-server .

# Run container
docker run -p 8080:8080 \
  -e AEM_BASE_URL="https://author-p12345-e67890.adobeaemcloud.com" \
  -e AEM_CLIENT_ID="your_client_id_here" \
  -e AEM_CLIENT_SECRET="your_client_secret_here" \
  aem-mcp-server

📦 Phase 1: Deploy to Vercel

See DEPLOYMENT_VERCEL.md for detailed instructions.

Quick steps:

# Install Vercel CLI
npm i -g vercel

# Deploy
vercel

# Add environment variables in Vercel dashboard
# Deploy to production
vercel --prod

Your API will be available at: https://your-project.vercel.app/api/mcp

🏗️ Phase 2: Deploy to Google Cloud Run

See DEPLOYMENT_CLOUDRUN.md for detailed instructions.

Option 1: Using GitHub Actions (Recommended)

1. Set up GCP and GitHub Secrets
2. Push to main branch - Automatically deploys
3. Service URL will be shown in Actions log

Option 2: Using Terraform

cd terraform

# Copy and edit variables
cp terraform.tfvars.example terraform.tfvars
nano terraform.tfvars

# Initialize Terraform
terraform init

# Preview changes
terraform plan

# Deploy infrastructure
terraform apply

Option 3: Manual Docker Deployment

# Build and tag
docker build -t gcr.io/YOUR_PROJECT/aem-mcp-server .

# Push to Container Registry
docker push gcr.io/YOUR_PROJECT/aem-mcp-server

# Deploy to Cloud Run
gcloud run deploy aem-assets-mcp-server \
  --image gcr.io/YOUR_PROJECT/aem-mcp-server \
  --platform managed \
  --region us-central1 \
  --allow-unauthenticated

🔧 Configuration

Environment Variables

Create a .env file