Skip to main content
Glama
nakulben

WhatsApp Business MCP

send_template_message

Send approved WhatsApp template messages to phone numbers using dynamic parameters for headers, body text, and media. Automate customer notifications from Claude, ChatGPT, and MCP-compatible AI clients.

Instructions

Send an approved template message to a phone number.

Args: to: Recipient phone number with country code (e.g. "+919876543210") template_name: Name of the approved template to send language: Language code matching the template (default "en") components: Optional list of component parameter dicts for dynamic values. Example for a template with header image and body params: [ {"type": "header", "parameters": [ {"type": "image", "image": {"link": "https://example.com/img.jpg"}} ]}, {"type": "body", "parameters": [ {"type": "text", "text": "John"}, {"type": "text", "text": "ORD-123"} ]} ]

Returns: JSON with message ID on success.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYes
template_nameYes
languageNoen
componentsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses the return value ('JSON with message ID on success') and the approval precondition, but omits safety classification (destructive/write nature), error handling behavior, rate limits, or authentication requirements.

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 docstring format with Args/Returns sections is well-structured and front-loaded with the core purpose. The components example is lengthy but necessary given the parameter's complex nested structure and lack of schema constraints; every element serves to clarify usage.

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

Completeness4/5

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

For a tool with 4 parameters and 0% schema coverage, the description adequately documents all inputs and the output format. It could be improved by mentioning error cases or explicitly contrasting with the bulk send sibling, but it covers the essential operational context.

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

Parameters5/5

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

Given 0% schema description coverage, the description provides exemplary compensation with detailed Args documentation. It includes format examples (country code phone format), default values (language 'en'), and a comprehensive nested structure example for the complex 'components' parameter that clarifies the expected object shape.

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 opening sentence 'Send an approved template message to a phone number' provides a specific verb, resource, and target. It implicitly distinguishes from sibling tools by emphasizing 'approved' (contrasting with create/validate templates) and singular 'phone number' (contrasting with send_bulk_template_messages).

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

Usage Guidelines3/5

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

The description mentions 'approved template,' hinting at a prerequisite workflow involving check_template_status or validate_template, but does not explicitly state when to use this single-send tool versus send_bulk_template_messages or provide alternative selection guidance.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/nakulben/whatsapp-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server