Quickstart

This guide provides the fastest route to running the sktime-mcp server and connecting it to a client.

1. Start the Server

Once installed, you can start the MCP server directly from your terminal:

sktime-mcp

By default, the server communicates over standard input/output (stdio).

2. Connect to a Client

To use sktime-mcp with an AI assistant, you must configure the client to launch the server.

Claude Desktop

Add the following configuration to your claude_desktop_config.json:

Linux: ~/.config/Claude/claude_desktop_config.json
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "sktime": {
      "command": "sktime-mcp"
    }
  }
}

Cursor or VS Code (MCP Extensions)

Configure the command sktime-mcp in the MCP settings section of your IDE or extension.

3. Verify Functionality

Once connected, you can verify the server is working by asking your assistant:

“What forecasting models are available in sktime?”

The assistant will use the list_estimators tool and return a list of available models for your review.

4. Run Your First Forecast

Try an end-to-end workflow by directing your assistant to use a built-in dataset:

“Load the ‘airline’ demo dataset and forecast the next 12 months using a NaiveForecaster.”

The assistant will handle the technical steps — locating the data, instantiating the model, and fitting it — before presenting the final predictions to you in the chat.

Next Steps

• Explore Core Concepts to understand how the system manages state.

• Refer to the User Guide for instructions on loading your own data and building pipelines.