DocumentationAEMAEM as a Cloud Service Tutorials

Search AEM Content Using the Content AI MCP Server

Last update: July 23, 2026
  • Applies to:
  • Experience Manager as a Cloud Service

CREATED FOR:

  • Beginner
  • Leader
  • User
  • Developer

Use the Content AI MCP Server from Adobe CX Coworker to search and analyze Content AI indexes in natural language, no low-level API code or UI navigation.

In this tutorial you discover available indexes, run keyword, semantic, and hybrid searches, and use natural language search to express complex intent, all from Adobe CX Coworker against a Content AI index.

Overview

AEM as a Cloud Service provides MCP Servers so your IDE or chat app can work with AEM securely. The Content AI MCP Server exposes search and discovery tools over Content AI indexes. See MCP Servers in AEM for more information.

The Content AI MCP Server provides six tools:

Tool
Purpose
list_indexes
Discover available indexes in your AEM environment.
get_index_config
Inspect the raw index configuration and metadata.
fulltext_search
Keyword-based search with fuzzy matching and field selection.
semantic_search
Vector-based similarity search for conceptual queries.
hybrid_search
Combined keyword + semantic search for the best general-purpose recall.
natural_language_search
Express intent in plain English; the server translates it into structured filters, ranges, and semantics.

The Content AI MCP Server supports two access modes, selected by which header you configure:

  • Public (anonymous) — Search public, read-only indexes using the X-Api-Key header. Use this for openly available, non-sensitive content. See Searching Public Indexes.
  • Authenticated — Search entitled or access-controlled indexes using the x-content-ai-mcp-api-key header together with your signed-in Adobe identity (passed through by CX Coworker). Results respect your permissions.

How Developers Can Use It

Connect Adobe CX Coworker to the Content AI MCP Server and run the scenario below.

Setup - Content AI MCP Server in Adobe CX Coworker

Let’s set up the Content AI MCP Server in Adobe CX Coworker with these steps.

  1. Sign in to Adobe CX Coworker.

    Adobe CX Coworker Sign In

  2. From the side rail, click MCP Servers.

    MCP Servers Side Rail

  3. Click Add MCP Server.

    Add MCP Server

  4. In the Add MCP Server dialog, enter the following details:

    table 0-row-2 1-row-2 2-row-2 3-row-2 4-row-2
    Field Value
    Server name content-ai-mcp
    MCP URL https://mcp.adobeaemcloud.com/adobe/experimental/aemagents-expires-20260331/mcp/content-ai
    Connection type HTTP
    Authentication type Passthrough

    Add MCP Server Dialog

    note
    NOTE
    Authentication type is set to Passthrough so CX Coworker forwards your signed-in Adobe identity to the MCP Server. You do not need a separate sign-in or OAuth step.

  5. Click Add headers and add the headers for the access mode you need:

    For public indexes (anonymous):

    table 0-row-2 1-row-2 2-row-2
    Header Value
    X-Api-Key Your public API key. Present this header when you only want to search public indexes.
    x-content-ai-mcp-routing (Optional) Environment/routing info, for example tier=publish,bucket=p12345-e67890,cluster=ethos21-prod-va7,namespace=ns-team-example.

    For non-public (entitled) indexes:

    table 0-row-2 1-row-2 2-row-2
    Header Value
    x-content-ai-mcp-api-key The API key from the Adobe Developer Console.
    x-content-ai-mcp-routing (Optional) Environment/routing info, for example tier=publish,bucket=p12345-e67890,cluster=ethos21-prod-va7,namespace=ns-team-example.
    note important
    IMPORTANT
    When the X-Api-Key header is present, the server treats the request as anonymous and only searches public indexes. Any signed-in identity is ignored, so there is no accidental escalation to authenticated access. Use x-content-ai-mcp-api-key (not X-Api-Key) when you intend to search entitled indexes.
    note
    NOTE
    If you do not set the x-content-ai-mcp-routing header, the server asks for your environment (tier and bucket) in chat the first time you run a tool, then retries automatically.

  6. Click Add. The content-ai-mcp server now appears in your list of MCP Servers.

    Content AI MCP Server Listed

  7. Click New chat to start using the Content AI MCP Server.

    New Chat

Searching Public Indexes

Some Content AI indexes are marked public and can be searched anonymously, without an entitled identity. Public indexes are read-only and are intended for openly available, non-sensitive content. Anyone with the public API key can search them.

Use this mode when:

  • You want to search openly available content (for example, public documentation or a demo catalog).
  • You do not need per-user, permission-scoped results.
  • You want a simple setup that only requires an API key.

To search public indexes, add the Content AI MCP Server in CX Coworker exactly as described in Setup - Content AI MCP Server in Adobe CX Coworker, but in the Add headers step add only the X-Api-Key header (plus an optional x-content-ai-mcp-routing header for the environment):

Header
Value
X-Api-Key
Your public API key.
x-content-ai-mcp-routing
(Optional) Environment/routing info, for example tier=publish,bucket=p12345-e67890.
IMPORTANT
When the X-Api-Key header is present, the server treats the request as anonymous and only searches public indexes. Any signed-in identity is ignored. Do not use X-Api-Key when you intend to search entitled indexes, use x-content-ai-mcp-api-key instead.

With the server connected, discover and search public indexes the same way as authenticated indexes.

  1. In CX Coworker, open a new chat and list the public indexes available to your API key:

    code language-text 
    List all Content AI indexes available in my environment.

    The server searches only public indexes for this request and returns matching results.

Summary

You set up the AEM Content AI MCP Server in Adobe CX Coworker and used it to search Content AI indexes. You discovered available indexes and searched them in natural language, using keyword, semantic, hybrid, and natural language search. You also learned how to search public indexes anonymously with an API key, and how to reduce response size with field selection. You can use the same human-centric flow from CX Coworker to search and analyze Content AI indexes without switching to a UI or writing low-level search API code.

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