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 CrewAI 12 tools — connect in under 2 minutes

Name: Flow XO
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 12 Tools Framework

Connect your CrewAI agents to Flow XO through the Vinkius — pass the Edge URL in the `mcps` parameter and every Flow XO tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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 crewai import Agent, Task, Crew

agent = Agent(
    role="Flow XO Specialist",
    goal="Help users interact with Flow XO effectively",
    backstory=(
        "You are an expert at leveraging Flow XO tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token — get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Flow XO "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 12 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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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.

When paired with CrewAI, Flow XO becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Flow XO tools autonomously — one agent queries data, another analyzes results, a third compiles reports — all orchestrated through the Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

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

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py — CrewAI auto-discovers 12 tools from Flow XO

Why Use CrewAI with the Flow XO MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Flow XO through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles — one agent researches, another analyzes, a third generates reports — each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass the Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Flow XO + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Flow XO for raw data, then a second analyst agent cross-references findings and flags anomalies — all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Flow XO, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Flow XO tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Flow XO against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Flow XO MCP Tools for CrewAI (12)

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

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

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

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts — check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

The Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Flow XO + CrewAI FAQ

Common questions about integrating Flow XO MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily — when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.