datawrapper-mcp

Name: datawrapper-mcp Review
Item: datawrapper-mcp
Rating: 3.0
Author: Aaron Matthews

Connector Data & Analytics Usable

Works inClaude Code Claude Cowork Claude Chat

Usable Scanned — metadata only

Embeds chart creation directly into AI workflows, enabling teams to generate publication-ready visualizations without context-switching to dedicated tools, r…

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

Generate interactive charts from raw data without leaving your analytics workflow
Ask Claude to create visualizations for quarterly revenue reports automatically
Build embeddable dashboards by describing your data structure to the AI

50 starsMIT (commercial OK)FreeNo code needed

Usable rating — This tool is functional but has notable gaps. Review the evaluation notes below before deploying.

Why it matters

Embeds chart creation directly into AI workflows, enabling teams to generate publication-ready visualizations without context-switching to dedicated tools, reducing time-to-insight for data-driven decision-making.

Best for

Data teams and analysts generating charts programmatically through AI assistants for reporting and dashboards.

Works in

Claude Code Claude Cowork Claude Chat

Source

https://github.com/palewire/datawrapper-mcp

By palewire

How to Get It

Option 1: Claude Desktop AppOpen the Customize panel in the sidebar → browse connectors → search and add. Works in Claude Code, Claude Cowork, and Claude Chat.

Option 2: Paste into Claude CodeCopy the command below and paste it into a Claude Code conversation. Claude will run it for you.

Command

claude mcp add datawrapper-mcp -- npx -y datawrapper-mcp

Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.

Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.

First thing to try

Once it’s connected, paste this into Claude:

Help me generate interactive charts from raw data without leaving my analytics workflow

CostFree

Trust Signals Auto-scanned

Stars50Last updated2026-09-12LicenseMIT (OK for commercial use)Known CVEsNone foundSources: GitHub Advisory Database + OSV.dev · Scanned 2026-09-13 · scanner v1

Data & Access

Data processingPrompts sent to Anthropic API. Enterprise/Team plans exclude training.

Community Pulse Quiet

No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.

Reviewer notes

Auto-scanned review. These are observations, not a security certification.

Scored from trust signals (evidence-eval-v1): 50 GitHub stars; contributors unknown; last commit 1d ago; license MIT.

Things to check

Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.

How to evaluate tools before deploying →

Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.

Evaluation Scores

Evaluation

Ease of Use

3/5

Versatility

3/5

Reliability

3/5

Security

3/5

Overall score3.00 / 5.00 UsableEvaluatedSep 2026

Scored from trust signals (evidence-eval-v1): 50 GitHub stars; contributors unknown; last commit 1d ago; license MIT.

← Back to the Claude Observatory