Datawrapper
Empowers AI assistants to create, update, and manage Datawrapper charts using natural language commands.
About
This Model Context Protocol (MCP) server acts as a bridge, allowing AI assistants to seamlessly generate and manipulate Datawrapper charts. Built upon the robust Datawrapper Python library and enhanced with Pydantic validation, it translates conversational prompts into dynamic data visualizations. Users can direct their AI to create new charts from datasets, publish them, update data points, modify visual styles, and even retrieve direct links or image embeds of the resulting graphics, streamlining the data storytelling process.
Key Features
- Programmatic updates to chart data and styling via AI commands
- Pydantic validation for robust data handling
- AI-driven Datawrapper chart creation from data
- 0 GitHub stars
- Ability to publish charts and retrieve public/editor URLs
- Embed PNG images of generated charts directly in responses
Use Cases
- Automating chart creation for news articles and reports using AI
- Enabling AI assistants to quickly visualize data during analysis sessions
- Streamlining the update process for recurring data visualizations through conversational prompts
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