Kontent.ai MCP Server

Name: Kontent.ai MCP Server
Author: kontent-ai

@kontent-ai

代码仓库主页

关于 Kontent.ai MCP Server

The Official Kontent.ai MCP server. Connect your AI with Kontent.ai.

#kontent-ai #mcp #content-management #headless-cms #cms

基本信息

分类

其他

许可证

MIT

运行时

node

传输方式

stdio

发布者

kontent-ai

提交者

mberry1989

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "kontent-ai-stdio": {
      "command": "npx",
      "args": [
        "@kontent-ai/mcp-server@latest",
        "stdio"
      ],
      "env": {
        "KONTENT_API_KEY": "<management-api-key>",
        "KONTENT_ENVIRONMENT_ID": "<environment-id>"
      }
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Kontent.ai MCP Server?

Kontent.ai MCP Server implements the Model Context Protocol to connect your Kontent.ai projects with AI tools like Claude, Cursor, and VS Code. It enables AI models to understand your content structure and perform operations through natural language instructions.

How to use Kontent.ai MCP Server?

Run the server with npx using the desired transport: npx @kontent-ai/mcp-server@latest stdio for local single‑tenant use, or npx @kontent-ai/mcp-server@latest shttp for a remote multi‑tenant server. For STDIO, configure credentials via environment variables (KONTENT_API_KEY, KONTENT_ENVIRONMENT_ID). For Streamable HTTP, pass the environment ID as a URL path parameter and the API key as a Bearer token.

Key features of Kontent.ai MCP Server

Rapid prototyping: transform diagrams into live content models in seconds
Data visualization: visualize your content model in any format
Manage content types, snippets, taxonomies, and languages
Create, update, and publish content items with variants
Manage content lifecycle workflows and roles
Search and bulk retrieve content item variants

Use cases of Kontent.ai MCP Server

Rapidly prototype content models from diagrams using natural language
Visualize and explore content models in any format
Create, edit, and manage content types, snippets, and taxonomies
Build and publish content items with full workflow control
Perform semantic searches across content item variants

FAQ from Kontent.ai MCP Server

What prerequisites are needed to run the server?

You need a Kontent.ai account, a project, a Management API key with appropriate permissions, and your environment ID.

What transports are available?

The server supports STDIO (single‑tenant, local) and Streamable HTTP (multi‑tenant, remote) transports.

How is authentication handled in each mode?

In STDIO mode, credentials are set via environment variables. In Streamable HTTP mode, the environment ID is part of the URL path and the API key is provided as a Bearer token per request.

Is there a risk of indirect prompt injection?

Yes. Content returned by the server can contain text that an LLM may interpret as instructions. Use a least‑privilege Management API key to limit the damage a hijacked agent can cause.