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Kommo CRM MCP Server

create_template

Create a chat template (e.g., WhatsApp waba) with message content, type, language, and category. Supports variables like {{contact.name}} for personalized messages.

Instructions

Cria um novo modelo de chat (template). Para WhatsApp, o type costuma ser 'waba'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesNome do modelo
typeNoTipo do modelo (ex: text, waba)text
contentYesCorpo da mensagem do modelo (pode usar variáveis como {{contact.name}})
client_slugYesIdentificador do cliente (slug)
is_editableNoSe usuários podem editar no app da Kommo
waba_categoryNoPara WhatsApp: UTILITY, AUTHENTICATION, MARKETING
waba_languageNoIdioma (ex: pt_BR)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of disclosing behavior. It states that the tool creates a new template, but does not mention side effects, validation behavior, required relationships (e.g., client_slug must reference an existing client), or WABA-specific requirements beyond a single type hint. A mutation tool like this needs more behavioral context.

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

Conciseness5/5

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

The description is only two sentences, with the primary purpose front-loaded in the first sentence and a helpful WhatsApp-specific hint in the second. No filler or redundant details are present.

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

Completeness2/5

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

There is no output schema, no annotations, and no usage guidance, so the description needs to provide more context than it does. For a 7-parameter create operation, it should at least mention prerequisites like an existing client_slug, explain WABA category/language expectations, or note what the tool returns. The current description is too thin to fully support correct invocation.

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?

The input schema covers 100% of parameters with descriptions, so the baseline is 3. The description adds a small extra hint that 'type' is usually 'waba' for WhatsApp, but it does not clarify interactions between type, waba_category, and waba_language. Since the schema already documents parameters well, the description offers only marginal added value.

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

Purpose4/5

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

The description uses a specific verb ('Cria') and resource ('novo modelo de chat (template)'), clearly indicating the tool creates a template. This differentiates it from sibling tools like get_templates, update_template, and delete_template. It could be slightly more precise about the relation between 'modelo' and 'template', but overall it is clear.

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

Usage Guidelines2/5

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

The description provides no explicit guidance on when to use this tool versus alternatives such as update_template or delete_template. The only additional context is a hint about the 'type' parameter for WhatsApp, which is parameter guidance rather than usage context. There are no prerequisites, exclusions, or scenario descriptions.

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