Datawrapper
平台与服务by palewire
基于 Model Context Protocol 的 MCP 服务器,可借助 AI 助手快速创建 Datawrapper 图表。
什么是 Datawrapper?
基于 Model Context Protocol 的 MCP 服务器,可借助 AI 助手快速创建 Datawrapper 图表。
README
A Model Context Protocol (MCP) server and app for creating Datawrapper charts using AI assistants. Built on the datawrapper Python library.
<!-- mcp-name: io.github.palewire/datawrapper-mcp -->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 |
常见问题
Datawrapper 是什么?
基于 Model Context Protocol 的 MCP 服务器,可借助 AI 助手快速创建 Datawrapper 图表。
相关 Skills
Slack动图
by anthropics
面向Slack的动图制作Skill,内置emoji/消息GIF的尺寸、帧率和色彩约束、校验与优化流程,适合把创意或上传图片快速做成可直接发送的Slack动画。
✎ 帮你快速做出适配 Slack 的动图,内置约束规则和校验工具,少踩上传与播放坑,做表情包和演示都更省心。
MCP构建
by anthropics
聚焦高质量 MCP Server 开发,覆盖协议研究、工具设计、错误处理与传输选型,适合用 FastMCP 或 MCP SDK 对接外部 API、封装服务能力。
✎ 想让 LLM 稳定调用外部 API,就用 MCP构建:从 Python 到 Node 都有成熟指引,帮你更快做出高质量 MCP 服务器。
接口测试套件
by alirezarezvani
扫描 Next.js、Express、FastAPI、Django REST 的 API 路由,自动生成覆盖鉴权、参数校验、错误码、分页、上传与限流场景的 Vitest 或 Pytest 测试套件。
✎ 帮你把API与集成测试自动化跑顺,减少回归漏测;能力全面,尤其适合复杂接口场景的QA团队。
相关 MCP Server
Slack 消息
编辑精选by Anthropic
Slack 是让 AI 助手直接读写你的 Slack 频道和消息的 MCP 服务器。
✎ 这个服务器解决了团队协作中需要 AI 实时获取 Slack 信息的痛点,特别适合开发团队让 Claude 帮忙汇总频道讨论或发送通知。不过,它目前只是参考实现,文档有限,不建议在生产环境直接使用——更适合开发者学习 MCP 如何集成第三方服务。
by netdata
io.github.netdata/mcp-server 是让 AI 助手实时监控服务器指标和日志的 MCP 服务器。
✎ 这个工具解决了运维人员需要手动检查系统状态的痛点,最适合 DevOps 团队让 Claude 自动分析性能数据。不过,它依赖 NetData 的现有部署,如果你没用过这个监控平台,得先花时间配置。
by d4vinci
Scrapling MCP Server 是专为现代网页设计的智能爬虫工具,支持绕过 Cloudflare 等反爬机制。
✎ 这个工具解决了爬取动态网页和反爬网站时的头疼问题,特别适合需要批量采集电商价格或新闻数据的开发者。不过,它依赖外部浏览器引擎,资源消耗较大,不适合轻量级任务。