How to Use the Flow XO MCP in Google ADK

Q: Can my Google ADK agent use Flow XO to send broadcast messages?

Yes, your agent can call sendpushmessage to send direct notifications to specific users. You can also monitor past campaigns using listbroadcasts.

Q: How does Flow XO help my Google ADK agent analyze bot performance?

The agent can call getautomationanalytics to pull performance metrics. You can feed this data directly into Vertex AI to spot trends or find issues.

Run enterprise chatbot automation and user management inside your Google ADK agent flows with this MCP Server.

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Connect Flow XO MCP to Google ADK

Create your Vinkius account to connect Flow XO 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 Flow XO with Google ADK

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Direct webhook triggers and workflow toggles

The `trigger_webhook` tool lets your Gemini agent fire off Flow XO sequences based on database events or analytical triggers. If a customer segment changes in BigQuery, your agent can kick off a re-engagement workflow instantly. You can also use `toggle_workflow` to pause or resume specific automations. It keeps your chat logic aligned with your real-time business rules without manual intervention.

Manage users across platforms with the MCP Server

The `list_chatbot_users` tool gives your agent a complete list of your end users across all connected channels. Your agent can query this list, find specific profiles, and run targeted campaigns. If you need to update a user's record, `update_user` lets you modify their tags or custom fields on the fly. This ensures your customer data remains consistent across Google Cloud and your chat platforms.

Audit conversation logs and platform connections

The `list_user_history` tool pulls the exact message history for any user so your agent has full context. This lets your Gemini model analyze past interactions to draft highly personalized responses. To keep track of where these messages are coming from, `list_bot_accounts` lists all your connected platforms. It helps your agent know exactly which channel to use when reaching out to a customer.

Setup guide

Set up Flow XO 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 Flow XO 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="Flow XO_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Flow XO 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 Flow XO. 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 Flow XO MCP in Google ADK

Use the McpToolset class with your server's HTTP URL. Pass that toolset into your LlmAgent constructor to expose the tools to Gemini. This lets your agent run the MCP Server tools directly.

Yes, your agent can call `send_push_message` to send direct notifications to specific users. You can also monitor past campaigns using `list_broadcasts`.

The agent can call `get_automation_analytics` to pull performance metrics. You can feed this data directly into Vertex AI to spot trends or find issues.

Yes, you can pass a list of allowed tool names to the toolset configuration. This prevents the agent from triggering workflows or modifying users if you want a read-only setup.

All analytics, user profile metadata, and workflow states are handled inside an ephemeral, zero-trust sandbox. We never store your customer data or API keys on our infrastructure.

Use it with your favorite AI tools

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