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 datawrapper-mcppip install datawrapper-mcpThis 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.
Ask AI
Ask AI about Datawrapper
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README
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.

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
- A Datawrapper account (sign up at https://datawrapper.de/signup/)
- An MCP client such as Claude or OpenAI Codex
- Python 3.10 or higher
Get Your API Token
- Go to https://app.datawrapper.de/account/api-tokens
- Create a new API token
- 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.