Create, manage, and explore your content and content model using natural language in any MCP-compatible AI tool.
Transform your content operations with AI-powered tools for Kontent.ai. Create, manage, and explore your structured content through natural language conversations in your favorite AI-enabled editor.
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.
Before you can use the MCP server, you need:
You can run the Kontent.ai MCP Server with npx:
npx @kontent-ai/mcp-server@latest stdio
npx @kontent-ai/mcp-server@latest sse
The server requires the following environment variables:
Variable | Description | Required |
---|---|---|
KONTENT_API_KEY | Your Kontent.ai Management API key | ✅ |
KONTENT_ENVIRONMENT_ID | Your environment ID | ✅ |
PORT | Port for SSE transport (defaults to 3001) | ❌ |
To run the server with STDIO transport, configure your MCP client with:
{
"kontent-ai-stdio": {
"command": "npx",
"args": ["@kontent-ai/mcp-server@latest", "stdio"],
"env": {
"KONTENT_API_KEY": "<management-api-key>",
"KONTENT_ENVIRONMENT_ID": "<environment-id>"
}
}
}
For SSE transport, first start the server:
npx @kontent-ai/mcp-server@latest sse
With environment variables in a .env
file, or otherwise accessible to the process:
KONTENT_API_KEY=<management-api-key>
KONTENT_ENVIRONMENT_ID=<environment-id>
PORT=3001 # optional, defaults to 3001
Then configure your MCP client:
{
"kontent-ai-sse": {
"url": "http://localhost:3001/sse"
}
}
For Streamable HTTP transport, first start the server:
npx @kontent-ai/mcp-server@latest shttp
With environment variables in a .env
file, or otherwise accessible to the process:
KONTENT_API_KEY=<management-api-key>
KONTENT_ENVIRONMENT_ID=<environment-id>
PORT=3001 # optional, defaults to 3001
Then configure your MCP client:
{
"kontent-ai-http": {
"url": "http://localhost:3001/mcp"
}
}
# Clone the repository
git clone https://github.com/kontent-ai/mcp-server.git
cd mcp-server
# Install dependencies
npm ci
# Build the project
npm run build
# Start the server
npm run start:sse # For SSE transport
npm run start:stdio # For STDIO transport
npm run start:shttp # For Streamable HTTP transport
# Start the server with automatic reloading (no need to build first)
npm run dev:sse # For SSE transport
npm run dev:stdio # For STDIO transport
npm run dev:shttp # For Streamable HTTP transport
src/
- Source code
tools/
- MCP tool implementationsclients/
- Kontent.ai API client setupschemas/
- Data validation schemasutils/
- Utility functions
errorHandler.ts
- Standardized error handling for MCP toolsthrowError.ts
- Generic error throwing utilityserver.ts
- Main server setup and tool registrationbin.ts
- Single entry point that handles both transport typesFor debugging, you can use the MCP inspector:
npx @modelcontextprotocol/inspector -e KONTENT_API_KEY=<key> -e KONTENT_ENVIRONMENT_ID=<env-id> node path/to/build/bin.js
Or use the MCP inspector on a running sse server:
npx @modelcontextprotocol/inspector
This provides a web interface for inspecting and testing the available tools.
MIT
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