Raghava Joijode

Posted on Feb 3

AI-Powered Content Management: Using MCP with AEM as a Cloud Service

#aem #ai #mcp

Whether you’re a developer orchestrating content workflows or a content author managing sites and assets, Adobe has integrated the Model Context Protocol (MCP) with AEM as a Cloud Service. This means you can now interact with AEM using natural language through AI tools like Claude, ChatGPT, Cursor, and Microsoft Copilot Studio—no API knowledge required.

What is MCP and Why Should You Care?

Model Context Protocol is a standardized way for applications to expose backend tools to Large Language Models (LLMs). Instead of manually crafting API calls, you can describe what you want in plain English, and the AI figures out which tools to use and how to chain them together.

Real example:
Instead of writing code to update content fragments across multiple pages, you can simply say:

“Update the hero banner for this spring campaign across all pages”

The LLM breaks this down, calls the right AEM MCP tools, and handles the implementation.

Who Benefits from MCP?

Different personas can leverage MCP in their preferred environments:

👨‍💻 Developers

Work in IDEs like Cursor to orchestrate content operations
Automate repetitive workflows with natural language commands
Integrate AEM operations into development pipelines

✍️ Content Authors & Practitioners

Manage sites, content fragments, and assets with AI assistance
Use familiar chat interfaces (ChatGPT, Claude) instead of AEM UI
Quickly find and update content across multiple pages

🏗️ Content Architects

Design and manage content fragment models
Coordinate large-scale content updates
Analyze content structure and relationships

Important: Authors should use the AI Assistant interface within AEM for operations that modify or delete content, as it includes built-in safeguards. MCP is better suited for developers orchestrating workflows and for read-only content exploration.

Key Benefits Across Teams

1. Natural Language Over Technical Complexity

No more memorizing API endpoints or AEM UI navigation paths. Describe what you need in plain English, and the AI handles the technical details.

Developer example:

“Create a new content fragment model for product reviews with fields for rating, title, and description”

Author example:

“Find all blog posts from last month that mention ‘sustainability’ and list their titles”

2. Consistent Experience Across Tools

Use the same AEM capabilities whether you’re in ChatGPT, Cursor, Claude, or Copilot Studio. Work in your preferred environment while accessing the same backend operations.

3. Security & Governance Preserved

All MCP operations run under your authenticated Adobe ID. Your existing AEM permissions apply—you can only do what you’re already authorized to do.

Available MCP Servers

Adobe provides two MCP endpoints at https://mcp.adobeaemcloud.com/adobe/mcp/:

Server	Endpoint	Purpose
Content	`/content`	Full CRUD operations for pages, fragments, and assets
Content (read-only)	`/content-readonly`	Safe read operations only

Supported Applications

AEM’s MCP integration works with:

✅ Anthropic Claude
✅ OpenAI ChatGPT
✅ Cursor IDE
✅ Microsoft Copilot Studio

Quick Setup Guide

Setting up MCP involves two steps:

Step 1: Configure Your MCP Client

The process is similar across all tools:

Add the AEM MCP Server URL
Example: https://mcp.adobeaemcloud.com/adobe/mcp/content-readonly
Authenticate with Adobe ID
You’ll be redirected to Adobe’s OAuth login
Your organization must permit the MCP client you’re using
Verify Tool Discovery
Once authenticated, the app discovers available AEM tools
You can list them by asking: “List all AEM MCP tools and what they do”

Step 2: Start Using It

Once configured, select the MCP server in your client and start prompting!

Real-World Workflows

Developer Workflows

Example 1: Automated Content Migration

Your prompt:

“List all content fragments using the old product model, export their data, and prepare a migration script to the new model”

What happens behind the scenes:

LLM lists all content fragment models
Searches for fragments using the specified model
Fetches fragment data including field values
Generates migration script with proper field mappings

Example 2: Environment Setup Verification

Your prompt:

“Check which environments are available and verify that all have the latest content fragment models deployed”

What happens:

Lists all environments and their licenses
Queries each environment for available models
Compares model versions across environments
Reports discrepancies

Content Author Workflows

Example 1: Bulk Content Updates

Your prompt:

“Update all product launch content fragments to reflect the new pricing for Q2”

What happens behind the scenes:

Searches for relevant content fragments
Resolves fragment paths to UUIDs
Fetches current fragment data
Applies updates using PATCH operations
Maintains optimistic concurrency with ETags

Example 2: Content Discovery & Publishing

Your prompt:

“Find all campaign banner images uploaded last week and show me which ones are published”

What happens:

Lists recent assets matching criteria
Filters by date and asset type
Checks publication status
Displays results with publishing state

Cross-Team Workflows

Example 3: Page Content Analysis

Your prompt:

“Get the hero banner content fragment used on the homepage and show me its current messaging”

What happens:

Retrieves page content
Extracts the fragment path
Resolves path to UUID
Fetches and displays fragment fields

Configuration Examples

For Developers: Cursor Setup

Ideal for developers who want AI assistance while coding:

Settings → MCP Servers
→ Add remote server
→ URL: https://mcp.adobeaemcloud.com/adobe/mcp/content
→ Complete Adobe OAuth flow
→ Enable/disable specific tools as needed

For Content Authors: Claude or ChatGPT Setup

Perfect for content teams who prefer chat-based workflows:

Claude:

Settings → Integrations → Model Context Protocol
→ Add server: https://mcp.adobeaemcloud.com/adobe/mcp/content-readonly
→ Authenticate with Adobe ID
→ Enable auto-confirm for read operations (optional)

ChatGPT:

Settings → Tools → Add MCP Server
→ URL: https://mcp.adobeaemcloud.com/adobe/mcp/content-readonly
→ Complete Adobe OAuth flow
→ Start querying your content

For Enterprise Teams: Microsoft Copilot Studio

Best for organizations wanting governed, shared access:

Create new agent → Tools → Add MCP Tool
→ URL: https://mcp.adobeaemcloud.com/adobe/mcp/content
→ Configure shared or dedicated connections
→ Set up auto-confirm or require user approval
→ Deploy across organization

Best Practices

⚠️ Critical Safety Note for Authors

Content authors should primarily use the AI Assistant interface within AEM for operations that modify or delete content. The AI Assistant has built-in safeguards specifically designed for content management scenarios.

MCP through external tools (ChatGPT, Claude, etc.) is powerful but requires more caution. Use it for:

✅ Content discovery and search
✅ Read-only analysis
✅ Exploring content structure
⚠️ Updates only after careful review

General Best Practices

1. Start with Read-Only for Exploration
Start with the /content-readonly endpoint when learning or exploring content. Switch to /content only when you need write access.

2. Review Before Confirming Writes
While some tools support auto-confirm, always review operations that modify or delete content. LLMs are powerful but not infallible.

3. Use Thinking Models for Complex Tasks
For multi-step operations or tasks involving different content types, enable “thinking mode” or similar features in your MCP client for better results.

4. Leverage Your Permissions
MCP respects your AEM role-based access. If you can’t do something manually in AEM, you can’t do it through MCP either.

Common Use Cases by Persona

For Developers

🔧 Environment Discovery: List available environments and licenses
🤖 Workflow Automation: Chain multiple operations for deployment pipelines
📊 Content Audits: Analyze content structure and model compliance
🔄 Bulk Migrations: Move content between models or environments

For Content Authors

📄 Content Search: Find pages and fragments by criteria
✏️ Quick Updates: Modify fragment fields across multiple instances
🖼️ Asset Management: Search, organize, and check publication status
📋 Content Reports: Generate lists of content matching specific criteria

For Content Architects

🧩 Model Management: Inspect and understand content fragment models
🔍 Structure Analysis: Map relationships between pages, fragments, and assets
📈 Usage Patterns: Identify which models and templates are most used
🎯 Governance: Ensure content follows established patterns and models

Authentication & Security

MCP uses OAuth integration with Adobe’s identity system:

Authenticate with your Adobe ID
System verifies the MCP client is permitted
Confirms the requested server is allowed
Issues tokens for subsequent tool calls
All operations respect your AEM permissions

This ensures AI-assisted work follows the same security model as manual operations.

Limitations to Know

Currently optimized for ChatGPT, Claude, Cursor, and MS Copilot Studio
Want to use a different client? Contact Adobe at aemcs-mcp-feedback@adobe.com
LLMs can occasionally produce inconsistent results—always verify outputs
Human oversight is essential, especially for production content

Managing MCP Access (Admins)

Administrators can:

Restrict specific MCP servers at organization, program, or environment level
Disable specific MCP clients based on organizational policies
Request support for additional clients by contacting Adobe

All MCP servers are allowed by default, and the four supported clients are pre-permitted.

Final Thoughts

MCP integration with AEM represents a fundamental shift in how different teams interact with content management systems:

Developers can orchestrate complex workflows using natural language instead of writing integration code
Content authors can query and explore content through familiar chat interfaces
Content architects can analyze and govern content structure more efficiently

The key is understanding which tool fits your workflow:

For developers: Cursor or Copilot Studio for IDE-integrated workflows
For content authors: ChatGPT or Claude for chat-based exploration (use AEM’s AI Assistant for content modifications)
For everyone: The /content-readonly endpoint for safe exploration

The technology is evolving rapidly. Tasks that require multiple prompts today may work seamlessly tomorrow. Start experimenting with read-only operations, build confidence, and always maintain human oversight for critical content operations.

Ready to get started?