How do I trigger a specific Flow XO workflow using the agent?

You can use the 'trigger_webhook' tool. Provide the Webhook URL generated by your Flow XO 'Webhook Trigger' and a JSON payload. The agent will post the data to that URL, starting the automated flow remotely.

What is a 'response path' and how do I get it?

A response path is a unique identifier for a user's conversation on a specific platform. You can find it by using the 'list_chatbot_users' or 'get_user_details' tools. It's required for sending push messages via the 'send_push_message' tool.

Can I disable a chatbot flow temporarily using the agent?

Yes! The 'toggle_workflow' tool allows you to enable or disable any of your flows by providing the Workflow ID and setting the 'active' parameter to true or false.

Flow XO MCP Server for Google ADK 12 tools — connect in under 2 minutes

Name: Flow XO
Availability: InStock
Author: Vinkius

google.github.io/adk-docs/tools/mcp-tools

Built by Vinkius GDPR 12 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Flow XO as an MCP tool provider through the Vinkius and your ADK agents can call every tool with full schema introspection.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
    StreamableHTTPConnectionParams,
)

# Your Vinkius token — get it at cloud.vinkius.com
mcp_tools = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    )
)

agent = Agent(
    model="gemini-2.5-pro",
    name="flow_xo_agent",
    instruction=(
        "You help users interact with Flow XO "
        "using 12 available tools."
    ),
    tools=[mcp_tools],
)

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Flow XO MCP Server

Connect your Flow XO account to any AI agent and automate your chatbot interactions and messaging workflows through the Model Context Protocol (MCP). Flow XO is a versatile platform for building and managing chatbots across various channels like Slack, Telegram, and the web. Now, you can manage your automation flows, oversee chatbot users, and trigger webhook-based workflows directly through natural conversation.

Google ADK natively supports Flow XO as an MCP tool provider — declare the Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 12 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.

What you can do

Workflow Management — List all your chatbot flows and toggle their active status (enable/disable) instantly.
User Oversight — Access your end-user database, fetch detailed profiles, and create or update user records.
Direct Messaging — Send push messages directly to users via their unique response paths from your chat interface.
Webhook Triggers — Push data payloads to Flow XO webhook trigger URLs to start automated sequences remotely.
Interaction History — Retrieve the message history for specific users to understand past bot engagements.
Platform Connectivity — List all connected bot accounts and platforms (Slack, Messenger, etc.) for better integration context.
Automation Analytics — Fetch high-level usage summaries and performance metrics for your chatbot environment.

The Flow XO MCP Server exposes 12 tools through the Vinkius. Connect it to Google ADK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Flow XO to Google ADK via MCP

Follow these steps to integrate the Flow XO MCP Server with Google ADK.

Install Google ADK

Run pip install google-adk

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Create the agent

Save the code above and integrate into your ADK workflow

Explore tools

The agent will discover 12 tools from Flow XO via MCP

Why Use Google ADK with the Flow XO MCP Server

Google ADK provides unique advantages when paired with Flow XO through the Model Context Protocol.

Google ADK natively supports MCP tool servers — declare a tool provider and the framework handles discovery, validation, and execution

Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Flow XO

Production-ready features like session management, evaluation, and deployment come built-in — not bolted on

Seamless integration with Google Cloud services means you can combine Flow XO tools with BigQuery, Vertex AI, and Cloud Functions

Flow XO + Google ADK Use Cases

Practical scenarios where Google ADK combined with the Flow XO MCP Server delivers measurable value.

Enterprise data agents: ADK agents query Flow XO and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine Flow XO tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query Flow XO regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Flow XO

Flow XO MCP Tools for Google ADK (12)

These 12 tools become available when you connect Flow XO to Google ADK via MCP:

create_user

get_automation_analytics

Get usage summary

get_user_details

Get user profile

list_bot_accounts

). List platform accounts

list_broadcasts

List sent broadcasts

list_chatbot_users

List all end users

list_user_history

List user messages

list_workflows

List automation flows

send_push_message

Send a push message

toggle_workflow

Enable/Disable a flow

trigger_webhook

Trigger flow via webhook

update_user

Update user metadata

Example Prompts for Flow XO in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with Flow XO immediately.

"List all my Flow XO chatbot users."

"Disable the workflow 'Old Customer Survey'."

"Send a push message to path 'abc/123': 'Your order has been shipped!'."

Troubleshooting Flow XO MCP Server with Google ADK

Common issues when connecting Flow XO to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

Flow XO + Google ADK FAQ

Common questions about integrating Flow XO MCP Server with Google ADK.

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.