How to Use the AvoSMS MCP in Google ADK

Q: Can I restrict which AvoSMS tools Google ADK exposes?

Pass the toolnames parameter when defining your toolset. This lets you hide destructive actions like deletesender while keeping basic read access open.

Q: How do I verify my AvoSMS account is active?

Run getaccountcheck through the agent. It confirms the connection status before you attempt to send thousands of messages.

Connect Gemini to AvoSMS via Google ADK to trigger text campaigns directly from BigQuery.

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Connect AvoSMS MCP to Google ADK

Create your Vinkius account to connect AvoSMS 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 AvoSMS with Google ADK

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Connect BigQuery to your AvoSMS MCP Server

Your enterprise data sits in Google Cloud. Your customers live on their phones. A Gemini agent can read a massive BigQuery table and automatically fire `add_contact` to build a fresh messaging list. Massive context windows mean you can dump entire customer histories into the prompt. The model analyzes past interactions before deciding exactly what to write when invoking `send_sms`.

Organize massive contact lists

Structuring outreach requires isolated groups via MCP. Gemini calls `create_list` to generate distinct buckets for different geographic regions or product interests. Auditing these groups happens through `list_lists`. When a campaign concludes, the agent triggers `delete_list` to keep your workspace free of stale records.

Monitor replies and credit limits

Long-running agents need to know their MCP resource constraints. Calling `get_balance` lets your script pause operations if you lack the funds for a massive broadcast. Reading inbound texts via `list_responses` feeds real-time feedback into Vertex AI. The framework parses the sentiment and decides whether a human operator needs to step in.

Setup guide

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AvoSMS. 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 AvoSMS MCP in Google ADK

You only need your Vinkius endpoint token. Create an McpToolset with StreamableHttpServerParameters and pass it to your LlmAgent tools array.

Pass the tool_names parameter when defining your toolset. This lets you hide destructive actions like delete_sender while keeping basic read access open.

The framework natively supports HTTP transports for remote servers. Your agent waits for the API to return success before moving to the next step.

Run get_account_check through the agent. It confirms the connection status before you attempt to send thousands of messages.

We run every execution in a zero-trust sandbox. Message payloads and sender IDs exist only in memory during the transaction, disappearing entirely once the connection closes.

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