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palewire

datawrapper-mcp

by palewire

get_chart

Read-onlyIdempotent

Retrieve an existing Datawrapper chart's complete configuration, metadata, and URLs to understand its styling, adapt it to a new dataset, or clone its appearance.

Instructions

⚠️ DATAWRAPPER MCP TOOL ⚠️ This is part of the Datawrapper MCP server integration.


Get information about an existing Datawrapper chart, including its complete configuration, metadata, and URLs.

The returned configuration can be used to:

  • Understand how a chart is styled and configured

  • Adapt the configuration to a new dataset

  • Clone a chart's styling to create similar visualizations

Returns:

  • chart_id: The chart's unique identifier

  • title: Chart title

  • type: Simplified chart type name (bar, line, stacked_bar, etc.) - same format as used in list_chart_types and create_chart

  • config: Complete Pydantic model configuration including all styling, colors, axes, tooltips, annotations, and other properties

  • public_url: Public URL if published

  • edit_url: Editor URL

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chart_idYesID of the chart to retrieve
access_tokenNoOptional Datawrapper API token. When provided, uses the caller's account. When omitted, falls back to the server's DATAWRAPPER_ACCESS_TOKEN env var.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, destructiveHint=false, etc. The description adds value by detailing the return structure and explaining how the configuration can be reused, enhancing understanding beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a warning header, clear bullet points for return values, and concise sentences. It could be slightly more compact but remains effective without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema (context says true), the description fully explains what the tool returns and its potential uses. No missing behavioral or contextual details for a read-only retrieval tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and already describes chart_id and access_token. The description does not add new parameter details or usage nuance beyond the schema, meeting the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states 'Get information about an existing Datawrapper chart' and enumerates returned fields (chart_id, title, type, config, URLs), clearly distinguishing it from sibling tools like create_chart, delete_chart, or update_chart.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context on when the returned configuration can be used (adapt styling, clone chart), but does not explicitly state when not to use this tool or name alternatives. It implies retrieval use rather than creation/modification.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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