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GUIPETAV

canva-mcp-server

by GUIPETAV

Exportar Design do Canva

canva_export_design

Exports a Canva design to PNG, JPG, PDF, PPTX, GIF, or MP4 by creating an asynchronous job, waits for completion, and returns the download URL(s).

Instructions

Exporta um design do Canva para um arquivo (PNG, JPG, PDF, PPTX, GIF ou MP4).

Cria um job de exportação assíncrono e aguarda (com polling, até ~30s) a conclusão antes de retornar.

Args:

  • design_id (string): id do design a exportar

  • format (enum): png | jpg | pdf | pptx | gif | mp4 (padrão: png)

Retorna a(s) URL(s) de download do arquivo exportado.

Exemplos:

  • "Exporte o design X como PDF" -> design_id="X", format="pdf"

Erros:

  • Se o job falhar ou exceder o tempo de espera, retorna uma mensagem explicando o que houve.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNoFormato de exportaçãopng
design_idYesID do design a exportar (retornado por canva_search_designs ou canva_create_design)
Behavior4/5

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

The description adds behavioral context beyond annotations: it mentions the asynchronous job, ~30s polling limit, and potential error handling. It does not contradict annotations and provides useful operational details.

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 sections for args, examples, and errors, and is front-loaded with purpose. It is slightly verbose but each part serves a clear function, keeping it efficient.

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?

Since there is no output schema, the description correctly specifies the return type (download URLs) and covers error scenarios. It is complete for a simple two-parameter tool, covering all necessary aspects.

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

Parameters4/5

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

Schema covers 100% of parameters, but the description adds value by noting that design_id comes from canva_search_designs or canva_create_design, and giving an example. This aids selection beyond the schema's basic descriptions.

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 clearly states it exports a Canva design to a file, listing supported formats. It distinguishes from sibling tools (search, create) by focusing on exporting, with a specific verb and resource.

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?

It explains the export process (async job, polling, timeout) and provides a clear example, though it does not explicitly contrast with sibling tools or give when-not-to-use scenarios. The context is sufficient to infer appropriate usage.

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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