mcp-wacli

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send_message

Send WhatsApp messages to phone numbers or contacts using the MCP-wacli server. This tool enables AI clients to transmit text messages through an authenticated WhatsApp session.

Instructions

Send a text message via WhatsApp.

Args:
    to: Recipient phone number (e.g. '573001234567') or JID
    message: Text message to send

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "to": "<to>",
      "message": "<message>"
    },
    "name": "send_message"
  }
}

Input Schema

Name	Required	Description	Default
`to`	Yes
`message`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Mar 9, 2026

TDQS

B3.1/5.0

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. It states the action ('send') but lacks critical behavioral details: whether this requires prior authentication (e.g., via auth_status), rate limits, error conditions (e.g., invalid number), or what happens on success/failure. For a mutation tool with zero annotation coverage, this is a significant gap.

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 highly concise and well-structured: a clear purpose statement followed by bullet-like parameter explanations. Every sentence earns its place, with no redundant or vague language. It's front-loaded with the core functionality.

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?

Given the tool's complexity (a mutation with no annotations, no output schema, and 2 parameters), the description is incomplete. It covers parameters well but misses behavioral context (e.g., authentication needs, side effects, error handling). For a WhatsApp messaging tool, this leaves the agent with insufficient information to use it reliably.

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?

The description adds meaningful semantics beyond the schema. The schema has 0% description coverage (just titles 'To' and 'Message'), but the description explains 'to' as 'Recipient phone number (e.g. '573001234567') or JID' and 'message' as 'Text message to send', including an example format. This compensates well for the low schema coverage.

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 clearly states the tool's purpose: 'Send a text message via WhatsApp.' It specifies the verb ('send') and resource ('text message'), and distinguishes it from sibling tools like send_file. However, it doesn't explicitly differentiate from other messaging tools (though none exist in siblings), so it's not a perfect 5.

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 guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication status), compare with send_file for file messages, or specify context like group vs. individual messaging. The agent must infer usage from the purpose alone.

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