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, Claude.ai, Cursor, VS Code Copilot, ChatGPT, OpenAI Codex, OpenClaw) 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 | Personal or org connector | streamable-http |
| Claude Code | Plugin marketplace or .mcp.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 |
| OpenClaw | ClawHub plugin or openclaw.json |
stdio |
1 maintainer
Metadata
1 maintainer
Release files for datawrapper-mcp 0.3.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| datawrapper_mcp-0.3.2.tar.gz | 1.2 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| datawrapper_mcp-0.3.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.2 MB
Release files / datawrapper_mcp-0.3.2.tar.gz
| Download URL | datawrapper_mcp-0.3.2.tar.gz |
|---|---|
| Size | 1.2 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
d4171d362f825866fd000ed4d0297f34445df65b7c8a0c6f3301758fd38da170
|
|
BLAKE2b-256 checksum How to use checksums |
bfdd8a144d88ca7042d7bc20a6b9ebbdfc833257aa929ddd204a4b2c8cd337de
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 12, 2026.
Transparency logRelease files / datawrapper_mcp-0.3.2-py3-none-any.whl
| Download URL | datawrapper_mcp-0.3.2-py3-none-any.whl |
|---|---|
| Size | 26.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
e18e7481f72ae3a591d29a73b99321f741da0565c1e4283e3ab06af0f636a645
|
|
BLAKE2b-256 checksum How to use checksums |
5443ec6cbc39d4c54f26486a693d0bca5572d37c5f18cf7fe021aff8e3529d67
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 12, 2026.
Transparency log
