How to Use the Gupshup Messaging MCP in Google ADK

Q: Can my Google ADK agent use Gupshup Messaging for reactive updates?

Certainly. Use sendreaction to confirm user input or sendtextmessage to follow up on a query. It keeps your agent's interactions feeling responsive.

Bring WhatsApp messaging to your Google ADK agents. Integrate Gupshup Messaging via this MCP Server.

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Connect Gupshup Messaging MCP to Google ADK

Create your Vinkius account to connect Gupshup Messaging 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 Gupshup Messaging with Google ADK

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Google ADK Integration for Messaging

Attach the server to your agent using the toolset interface. Your agent gains the ability to interact with WhatsApp users as part of its standard execution flow. It works alongside your BigQuery data. You can query customer records and trigger a `send_template_message` in one sequence.

High-Volume Message Handling

Leverage the long-context memory of Gemini to manage complex conversations. Use `send_interactive_message` to provide structured options to your users. The server handles the translation into the required JSON format. Your agent stays focused on high-level reasoning.

Infrastructure-Ready Messaging

The setup supports both Stdio and HTTP transports to fit your Google Cloud environment. It is built to run reliably in your existing agent infrastructure. Use `get_template_info` to verify template status before dispatching content. This ensures you only send messages that meet current policy guidelines.

Setup guide

Set up Gupshup Messaging 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 Gupshup Messaging 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="Gupshup Messaging_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Gupshup Messaging tools via MCP.",
    tools=mcp_tools,
)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Gupshup. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Gupshup Messaging MCP in Google ADK

Use the McpToolset class to point to your server URL. Once added to the agent's tool list, your model can trigger any of the six messaging tools.

It does. The server is designed to run as a sidecar or a remote service. You can restrict which tools your agent accesses by filtering the tool list.

Certainly. Use `send_reaction` to confirm user input or `send_text_message` to follow up on a query. It keeps your agent's interactions feeling responsive.

It is. Since your agent has access to both your database tools and this messaging server, you can build workflows that pull data and message users automatically.

The server only processes the specific payloads you send. It does not persist message history or user phone numbers, keeping your data footprint limited to the API transaction.

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