How to Use the WhatsApp Message Sender MCP in Google ADK

Use WhatsApp Message Sender with Google ADK.

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Connect WhatsApp Message Sender MCP to Google ADK

Create your Vinkius account to connect WhatsApp Message Sender to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup WhatsApp Message Sender with Google ADK

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Actioning Messages via MCP Server

The `send_whatsapp_message` tool lets your agent send a text message using the Meta Cloud API. You simply pass the destination phone number in E.164 format and the message body to trigger it. This gives agents built on Google ADK direct, actionable access to customer communication channels.

Deep Integration with Enterprise Data

Because your agent runs on Google Cloud, you can use the data stored in BigQuery to determine who needs a message. You feed that context into `send_whatsapp_message` right when it's needed. It makes sending messages an outcome of complex reasoning, not just a standalone action.

Large Context Reasoning for Messaging

Gemini models within the Google ADK can hold massive context (1M+ tokens). This means your agent can analyze huge amounts of customer history before deciding to send a message using `send_whatsapp_message`. It builds sophisticated reasoning pathways, ensuring every WhatsApp Message Sender action is fully justified by the data.

Setup guide

Set up WhatsApp Message Sender MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with WhatsApp Message Sender tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="WhatsApp Message Sender_agent",
    model="gemini-2.0-flash",
    instruction="You have access to WhatsApp Message Sender tools via MCP.",
    tools=mcp_tools,
)

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Common questions about WhatsApp Message Sender MCP in Google ADK

You expose the MCP Server as a toolset to your LlmAgent. The agent then calls `send_whatsapp_message` when its reasoning dictates that a message must be sent.

Remember, sending outside the 24-hour service window requires pre-approved templates on Meta's side. The tool itself is only for text messages and relies on the official Cloud API.

The server touches customer phone numbers in E.164 format and the message body text. These parameters are passed to `send_whatsapp_message` by your agent.

It's designed for precise, context-driven messaging. While you can process lists of numbers through BigQuery, the tool executes one message send at a time via `send_whatsapp_message`.

You'll want to check your Vertex AI logs and BigQuery history. This is where the agent records its decision-making process leading up to the `send_whatsapp_message` call.

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