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 LangChain 12 tools — connect in under 2 minutes

Name: Flow XO
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 12 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Flow XO through the Vinkius and LangChain agents can call every tool natively — combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "flow-xo": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Flow XO, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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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.

LangChain's ecosystem of 500+ components combines seamlessly with Flow XO through native MCP adapters. Connect 12 tools via the Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures — with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain via MCP

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

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 12 tools from Flow XO via MCP

Why Use LangChain with the Flow XO MCP Server

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

The largest ecosystem of integrations, chains, and agents — combine Flow XO MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Flow XO queries for multi-turn workflows

Flow XO + LangChain Use Cases

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

RAG with live data: combine Flow XO tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Flow XO, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Flow XO tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Flow XO tool call, measure latency, and optimize your agent's performance

Flow XO MCP Tools for LangChain (12)

These 12 tools become available when you connect Flow XO to LangChain 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 LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Flow XO + LangChain FAQ

Common questions about integrating Flow XO MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.