Datawrapper MCP Server

Example Use Cases

• 1

  Create and publish Datawrapper charts programmatically via conversational interfaces.

• 2

  Update chart data and configuration dynamically through chat commands.

• 3

  Integrate Datawrapper chart management into AI workflows or Kubernetes deployments.

Description

This MCP server allows AI assistants to create, publish, update, and display Datawrapper charts using the Datawrapper Python library with Pydantic validation. It supports integration with MCP clients like Claude and OpenAI Codex, and can be deployed locally or on Kubernetes. The server facilitates seamless chart management through conversational commands, enhancing automation and productivity for users working with Datawrapper charts.