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GUIPETAV

canva-mcp-server

by GUIPETAV

Criar Design no Canva

canva_create_design

Create a new blank Canva design using preset types like presentation, poster, or flyer. Returns the design ID and edit link for immediate use.

Instructions

Cria um novo design em branco no Canva a partir de um preset de tipo/tamanho.

Esta é uma ferramenta de escrita: cria um recurso novo e persistente na conta do Canva do usuário.

Args:

  • title (string): título do design

  • design_type (enum): um dos presets suportados (presentation, doc, poster, instagram_post, instagram_story, facebook_post, logo, flyer)

Retorna o id do design criado e o link de edição no Canva.

Exemplos:

  • "Crie uma apresentação chamada 'Aula 1 - Introdução'" -> title="Aula 1 - Introdução", design_type="presentation"

  • Não use para gerar conteúdo com IA a partir de um prompt de texto — esta ferramenta cria apenas um design em branco

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYesTítulo do novo design (ex: 'Poster - Aula Mídias Criativas com IA')
design_typeYesTipo de preset de design a criar: presentation, doc, poster, instagram_post, instagram_story, facebook_post, logo, flyer
Behavior4/5

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

Annotations already indicate a non-read-only, non-idempotent, non-destructive operation. The description adds behavioral context: clarifies it is a 'ferramenta de escrita' that creates a persistent resource and returns the design id and edit link. This aligns with annotations and enriches the agent's understanding beyond the structured hints.

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 purpose statement, write-tool note, args, return value, and examples. It is slightly redundant with the schema in the Args section, but every section adds context. Front-loads the core purpose and negative usage, making 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?

For a tool with only 2 params, no output schema, and moderate annotations, the description covers the essential aspects: what it creates, parameter semantics, return value, and a key exclusion. It is complete enough for an agent to decide when and how to invoke it.

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 coverage is 100% and includes descriptions for both params. The description adds value by providing a natural-language example mapping ('Crie uma apresentação chamada...' -> title/design_type) and summarizing the enum values. This helps the agent understand how to translate user requests into parameters.

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 states a specific verb and resource: 'Cria um novo design em branco no Canva a partir de um preset de tipo/tamanho.' This clearly differentiates from sibling tools (search, export) since creating a blank design is a distinct action. It also specifies the scope and output.

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 clear context and a when-not: 'Não use para gerar conteúdo com IA a partir de um prompt de texto — esta ferramenta cria apenas um design em branco.' It does not explicitly mention alternatives like search or export, but the primary use case and exclusion are stated.

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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