Vexa
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AEM MCP server. Chat with your AEM instance for content, component, and asset operations.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"aem": {
"command": "npx",
"args": [
"-y",
"aem-mcp-server"
]
}
}
}在终端中运行这条命令
claude mcp add aem -- npx -y aem-mcp-server粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"aem": {
"command": "npx",
"args": [
"-y",
"aem-mcp-server"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"aem": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"aem-mcp-server"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日
注册名称已通过 GitHub 账户 easingthemes 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(1.3.9)于9个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。
同一分类中有:Vexa, emailmd, MCP WhatsApp Cloud
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Meeting bot and transcripts for Google Meet, Teams and Zoom. Live or after, speakers labelled.
Render markdown into email-safe HTML, lint drafts for deliverability problems, and preview emails.
MCP server for WhatsApp Cloud API (Meta) — messages, media, and templates via Graph API
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
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.
npx (recommended, zero install) and streamable HTTPNo 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) orenvFile|
| Cursor |
${env:AEM_PASSWORD}|
Example with env var references (Claude Code):
`json
{
"mcpServers": {
"AEM": {
"command": "npx",
"args": ["-y", "aem-mcp-server", "-t", "stdio", "-H", "${AEM_HOST:-http://localhost:4502}", "-u", "${AEM_USER:-admin}", "-p", "${AEM_PASSWORD:-admin}"]
}
}
}
`
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" } } }
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:
clientId and clientSecret for OAuth S2S authentication. More info.user/pass. Default credentials are admin: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.
resources/list, eliminating discovery roundtripsgroup, readOnly, and complexity so agents can make smarter tool selection decisionsverbosity parameter (summary/standard/full) on content-reading tools strips JCR internals and truncates long textsuggestion and alternatives fields for self-healing agent workflowsmanageContentFragment action mergeJsonField) for CFs that store a whole key→value map inside one JSON-encoded fieldOnce configured in your AI IDE, just ask in natural language:
List all components on MyPage
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/ /.../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.
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.
For detailed API documentation, please refer to the API Docs.