About aem-mcp-server
aem-mcp-server connects AI agents to Adobe Experience Manager for natural-language management of content, components, assets, and workflows. It supports AEMaaCS and self-hosted instances, including connections to multiple instances.
Key features
- 0157 tools for AEM operations
- 02Content and experience fragment management
- 03Search, publishing, and workflow controls
- 04Read-only resources for AEM catalogs
- 05Multiple instance connections
- 06Basic auth and OAuth S2S
Use cases
- 01Managing AEM content through natural language
- 02Searching pages and content fragments
- 03Publishing content and advancing workflows
- 04Working across multiple AEM instances
MCP support
The server exposes 57 MCP tools and read-only resources for AEM components, sites, templates, and workflow models. It supports stdio and streamable HTTP transports.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEAEM MCP Server (aem-mcp-server)
AEM MCP Server is a full-featured Model Context Protocol (MCP) server for Adobe Experience Manager (AEM). It provides a simple integration with any AI Agent. This project is designed for non-technical persons who want to manage AEM via natural language.
Overview
- Manage your AEM instance with natural language — content, components, assets, workflows
- Works with any MCP-compatible client:
- AI IDEs — Cursor, VS Code + Copilot, Windsurf, Cline, JetBrains AI Assistant, Zed
- CLI agents — Claude Code, GitHub Copilot CLI, Gemini CLI, Amazon Q CLI
- Chat & desktop apps — Claude Desktop, ChatGPT Desktop, Goose
- Supports both AEMaaCS and self-hosted AEM instances
- Two transport modes — stdio via
npx(recommended, zero install) and streamable HTTP
Quick Start
Prerequisites
- Node.js 20.19.0+ || 22.12.0+ || 23+
- Access to an AEM instance (local or remote)
Stdio Transport (recommended)
No installation needed — the AI agent downloads and spawns the process automatically via npx.
Add to your project's MCP config (.mcp.json, .vscode/mcp.json, .cursor/mcp.json, etc.):
{
"mcpServers": {
"AEM": {
"command": "npx",
"args": ["-y", "aem-mcp-server", "-t", "stdio", "-H", "http://localhost:4502", "-u", "admin", "-p", "admin"]
}
}
}
Secrets: Since MCP config files are typically committed to the repo, avoid hardcoding credentials. Use your client's env var syntax instead:
Client Syntax Claude Code ( .mcp.json)${AEM_PASSWORD}or${AEM_PASSWORD:-admin}VS Code / Copilot ${input:aem-password}(prompts securely) orenvFileCursor ${env:AEM_PASSWORD}Example with env var references (Claude Code):
{ "mcpServers": { "AEM": { "command": "npx", "args": ["-y", "aem-mcp-server", "-t", "stdio", "-H", "${AEM_HOST:-http://localhost:4502}", "-u", "${AEM_USER:-admin}", "-p", "${AEM_PASSWORD:-admin}"] } } }
Streamable HTTP Transport (alternative)
For scenarios where you need a persistent server (shared team server, multiple clients connecting simultaneously, etc.), install globally and start the server manually:
npm install aem-mcp-server -g
aem-mcp -H=http://localhost:4502 -u=admin -p=admin
Then point your AI agent to the URL:
{
"mcpServers": {
"AEM": {
"url": "http://127.0.0.1:8502/mcp"
}
}
}
Configuration
Options:
--version Show version number [boolean]
-H, --host [string] [default: "http://localhost:4502"]
-u, --user [string] [default: "admin"]
-p, --pass [string] [default: "admin"]
-i, --id clientId [string] [default: ""]
-s, --secret clientSecret [string] [default: ""]
-m, --mcpPort [number] [default: 8502]
-t, --transport Transport mode: http (default) or stdio
[string] [choices: "http", "stdio"] [default: "http"]
-I, --instances Named AEM instances: "local:http://localhost:4502:admin:admin
,qa:https://qa.example.com:user:pass" [string] [default: ""]
-h, --help Show help [boolean]
Authentication:
- For AEMaaCS, use
clientIdandclientSecretfor OAuth S2S authentication. More info. - For self-hosted AEM, use
user/pass. Default credentials areadmin:admin.
Multi-instance: Connect to multiple AEM instances simultaneously:
aem-mcp --instances "author:http://localhost:4502:admin:admin,publish:http://localhost:4503:admin:admin"
All tools will get an instance parameter to target a specific instance.
Features
- 57 MCP Tools covering pages, components, assets, workflows, content fragments, and experience fragments
- MCP Resources — agents discover components, sites, templates, and workflow models upfront via
resources/list, eliminating discovery roundtrips - Tool Annotations — every tool tagged with
group,readOnly, andcomplexityso agents can make smarter tool selection decisions - Response Verbosity —
verbosityparameter (summary/standard/full) on content-reading tools strips JCR internals and truncates long text - Actionable Errors — error responses include
suggestionandalternativesfields for self-healing agent workflows - Component Operations: Update, scan, add, convert, and bulk-manage AEM components (including Experience Fragments)
- Content & Experience Fragments: Full CRUD + variation management for both CF and XF, plus server-side JSON-string field merging (
manageContentFragmentactionmergeJsonField) for CFs that store a whole key→value map inside one JSON-encoded field - Advanced Search: QueryBuilder, fulltext, fuzzy, and enhanced page search
- Replication & Workflows: Publish/unpublish content, start/advance/delegate workflow stages
- Text & Image Extraction: Extract all text and images from pages, including fragments
- Template & Structure Discovery: List templates, analyze page/component structure
- Multi-instance: Connect to multiple AEM instances simultaneously; tools and resources are instance-aware
- Security: Basic auth and OAuth S2S, environment-based config, safe operation defaults
Usage
Once configured in your AI IDE, just ask in natural language:
List all components on MyPage
Merging into a JSON-string field
Some Content Fragments store an entire key→value map inside a single field as a JSON-encoded
string. To upsert a few keys without round-tripping the whole blob, use the mergeJsonField
action — the read-merge-write happens server-side:
{
"action": "mergeJsonField",
"fragmentPath": "/content/dam/<site>/.../labels",
"field": "CFMValue", // the field holding the JSON string
"jsonPointer": "/0/content/0/value", // RFC-6901 pointer to the object to merge into ("" = field root)
"merge": { "search": "Search", "clear_search": "Clear search" },
"variation": "master" // default: master
}
New keys are added, existing keys overwritten (deep-merge), and untouched keys preserved. The response reports the keys added/overwritten and the before/after key count at the pointer.
MCP Resources
The server exposes read-only MCP resources so agents can discover AEM catalogs without tool calls:
| Resource URI | Description |
|---|---|
aem://{instance}/components | All components (name, resourceType, title, group) |
aem://{instance}/sites | Site roots and language structure under /content |
aem://{instance}/templates | Available page templates (path, title) |
aem://{instance}/workflow-models | Workflow models (ID, title, description) |
Resources return summary data only. In multi-instance mode, each instance gets its own set of resource URIs.
API Documentation
For detailed API documentation, please refer to the API Docs.
Similar Projects
- https://github.com/easingthemes/aem-mcp-server (Used as a base for this project)
- https://github.com/indrasishbanerjee/aem-mcp-server (Used as a base for #1)
- https://www.npmjs.com/package/@myea/aem-mcp-handler (Looks like an original source of #2)
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.