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MCP server · AI

Datawrapper

A Model Context Protocol (MCP) server for creating Datawrapper charts using AI assistants

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Scored 7 months ago · breakdown

About Datawrapper

Datawrapper is an MCP server published by palewire in the AI category: a Model Context Protocol (MCP) server for creating Datawrapper charts using AI assistants.

The repository has 60 stars and 13 forks, with the last commit 23 days ago. Recent commit activity is the strongest signal that reported issues will get attention.

Install

uvx
uvx datawrapper-mcp
pip
pip install datawrapper-mcp

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Tools (8)

create_chartCreate a new chart with data and configuration

Parameters not published.

delete_chartPermanently delete a chart

Parameters not published.

export_chart_pngExport a chart as a PNG image

Parameters not published.

get_chartRetrieve a chart's configuration and metadata

Parameters not published.

get_chart_schemaGet the full configuration schema for a chart type

Parameters not published.

list_chart_typesList available chart types with descriptions

Parameters not published.

publish_chartPublish a chart to make it publicly accessible

Parameters not published.

update_chartUpdate an existing chart's data or styling

Parameters not published.

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Security checks

  • ✓README presentThe repository ships documentation.

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README

PyPI MCP Registry Docker Hub

A Model Context Protocol (MCP) server and app for creating Datawrapper charts using AI assistants. Built on the datawrapper Python library.

Example Usage

You can provide a data file and simply ask for the chart you want. The draft will soon appear in the panel.

Books chat chart

Here's a more complete example showing how to create, publish, update, and display a chart by chatting with the assistant:

"Create a datawrapper line chart showing temperature trends with this data:
2020, 15.5
2021, 16.0
2022, 16.5
2023, 17.0"
# The assistant creates the chart and returns the chart ID, e.g., "abc123"

"Publish it."
# The assistant publishes it and returns the public URL

"Update chart with new data for 2024: 17.2°C"
# The assistant updates the chart with the new data point

"Make the line color dodger blue."
# The assistant updates the chart configuration to set the line color

"Show me the editor URL."
# The assistant returns the Datawrapper editor URL where you can view/edit the chart

"Show me the PNG."
# The assistant embeds the PNG image of the chart in its contained response.

"Suggest five ways to improve the chart."
# See what happens!

Tools

Tool Description
list_chart_types List available chart types with descriptions
get_chart_schema Get the full configuration schema for a chart type
create_chart Create a new chart with data and configuration
update_chart Update an existing chart's data or styling
publish_chart Publish a chart to make it publicly accessible
get_chart Retrieve a chart's configuration and metadata
delete_chart Permanently delete a chart
export_chart_png Export a chart as a PNG image

Chart Types

bar, line, area, arrow, column, multiple column, scatter, stacked bar

Use list_chart_types to see descriptions, then get_chart_schema to explore configuration options for any type.

Getting Started

Requirements

Get Your API Token

  1. Go to https://app.datawrapper.de/account/api-tokens
  2. Create a new API token
  3. Add it to your MCP configuration as shown in the installation guide

Quick Start (Claude Code)

{
  "mcpServers": {
    "datawrapper": {
      "command": "uvx",
      "args": ["datawrapper-mcp"],
      "env": {
        "DATAWRAPPER_ACCESS_TOKEN": "your-token-here"
      }
    }
  }
}

For other clients (Claude Desktop, Cursor, VS Code Copilot, ChatGPT, OpenAI Codex) and Kubernetes deployment, see the installation guide.

Using Your Own Token (Hosted Deployments)

When connecting to a hosted instance of the server over HTTP, you can authenticate with your own Datawrapper API token by sending it in the Authorization header:

Authorization: Bearer <your-datawrapper-api-token>

This ensures charts are created under your account instead of the server operator's. The token is read from the header automatically — no need to include it in every tool call.

You can also pass access_token directly as a tool argument, which takes precedence over the header. When neither is provided, the server falls back to its DATAWRAPPER_ACCESS_TOKEN environment variable.

Supported Clients

Client Config file Transport
Claude Desktop claude_desktop_config.json stdio or streamable-http
Claude.ai Managed connector streamable-http
Claude Code .claude/settings.json stdio
VS Code Copilot .vscode/mcp.json stdio
Cursor .cursor/mcp.json stdio or streamable-http
ChatGPT Dev Mode settings streamable-http only
OpenAI Codex ~/.codex/config.toml stdio

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About Datawrapper

How do I install Datawrapper?

Run uvx datawrapper-mcp, then add the server to your MCP client's configuration.

Is Datawrapper safe to use with an AI agent?

Its trust score is 37 out of 100 (low). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Datawrapper still maintained?

Yes — the last commit was 23 days ago. The repository has 60 stars and 13 forks.