Flow XO MCP. Manage users and automate your chatbot backend from chat.
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Flow XO MCP Server connects your AI agent to your chatbot platform. It lets you manage user accounts, check conversation history, and run complex automation workflows across Slack, Telegram, and custom webhooks.
You can list all active flows, update user data, send direct messages, and see usage analytics, all without leaving your AI client.
What your AI agents can do
Create user
Registers a new user account in your chatbot system.
Get automation analytics
Fetches a usage summary of your chatbot platform's performance.
Get user details
Retrieves the full profile and metadata for a specific end user.
Creates new user profiles, retrieves existing user details, and updates user metadata across the platform.
Lists all existing chatbot workflows and enables or disables them instantly. You can also remotely trigger a workflow using a webhook.
Sends immediate push notifications directly to a user's unique response path within your chat interface.
Fetches the message history for any specific user, allowing you to review past bot engagements.
Retrieves high-level usage summaries and analytics for your entire chatbot environment.
Lists all linked bot accounts and platforms (e.g., Slack, Messenger) to provide context for integration.
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Flow XO MCP Server: 12 Tools for Chatbot Management
These 12 tools let your AI agent perform every core function of your chatbot backend—from creating users to triggering complex, multi-step workflows—all in one place.
019d759ccreate user
Registers a new user account in your chatbot system.
019d759cget automation analytics
Fetches a usage summary of your chatbot platform's performance.
019d759cget user details
Retrieves the full profile and metadata for a specific end user.
019d759clist bot accounts
Lists all external platforms and accounts connected to your chatbot system.
019d759clist broadcasts
Retrieves a list of messages that have been sent as broadcasts.
019d759clist chatbot users
Lists all end-user accounts currently registered in your chatbot database.
019d759clist user history
Retrieves the message history for a specified user, detailing past interactions.
019d759clist workflows
Retrieves a list of all defined automation flows (workflows) in your chatbot system.
019d759csend push message
Sends a single, immediate push message to a specified user path.
019d759ctoggle workflow
Changes the active status (on/off) of a specific chatbot workflow.
019d759ctrigger webhook
Sends a data payload to a specific webhook URL to start an automated flow.
019d759cupdate user
Changes metadata or details for an existing user account.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Flow XO, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
Flow XO MCP Server connects your AI agent directly to your chatbot platform. You'll manage user accounts, check conversation history, and run complex automation workflows across Slack, Telegram, and custom webhooks without ever leaving your AI client. You can list all active flows, update user data, send direct messages, and see usage analytics—all in one spot. Manage user records by using create_user to register a new user, get_user_details to pull a specific user's full profile, update_user to change their metadata, and list_chatbot_users to see every account registered in the chatbot database. Control automation flows by listing all defined workflows with list_workflows, turning them on or off instantly using toggle_workflow, or kicking off a sequence manually with trigger_webhook. Send targeted messages immediately to a user's unique response path using send_push_message.
You can audit conversation history for any user by calling list_user_history to review their past bot interactions. View platform performance by fetching a usage summary and analytics for the entire chatbot environment using get_automation_analytics. List and modify connected accounts by calling list_bot_accounts to see every platform linked to the chatbot system, and you can also review every message sent as a broadcast using list_broadcasts.
How Flow XO MCP Works
- 1 Subscribe to the Flow XO server on the Vinkius Marketplace and provide your Flow XO API Key.
- 2 Your AI agent invokes a tool (e.g.,
get_user_details) and provides necessary parameters like a user ID. - 3 The Flow XO server executes the action and returns the structured data or confirmation to your AI agent.
The bottom line is, your AI client treats your entire chatbot backend like a set of functions it can call.
Who Is Flow XO MCP For?
The Customer Success Manager who needs to check a user's profile or send a follow-up message without logging into a separate dashboard. The Automation Specialist who needs a real-time overview of active flows and triggers sequences with simple AI commands. The Marketing Operations person who needs to push data payloads to webhooks for lead generation and nurturing.
Checks user profiles using get_user_details or sends direct follow-up messages via send_push_message to keep users engaged.
Gets a real-time overview of active flows using list_workflows and triggers sequences via trigger_webhook to test automation logic.
Automates lead nurturing by pushing data payloads to chatbot webhooks using trigger_webhook.
What Changes When You Connect
- Manage user data immediately. Don't jump through dashboards. Use
get_user_detailsorupdate_userto check or change a profile right from your conversation. - Control automation on the fly. Use
list_workflowsto see all flows, thentoggle_workflowto disable a broken sequence instantly. This is faster than logging into the Flow XO dashboard. - Deep conversation context. Instead of guessing what happened, run
list_user_historyto pull the full message thread for any user. You know exactly where they left off. - Remote workflow triggers. Need to kick off a sequence for a lead? Use
trigger_webhookto push a data payload and start the automation without any manual UI interaction. - Targeted communications. Send a follow-up message instantly using
send_push_messageto a specific user path, ensuring the user gets the message right when they expect it. - System visibility. Get a high-level performance check with
get_automation_analyticsto see how the whole system is performing, or list all connected accounts withlist_bot_accounts.
Real-World Use Cases
Investigating a user's complaint
A customer reports an issue. Instead of asking a colleague to manually check the user's record, your agent runs get_user_details. The agent sees the user's last login date and then runs list_user_history to pull the last 20 messages, immediately giving the support team the full context needed to resolve the issue.
Testing a new marketing flow
Marketing Ops builds a new lead-nurturing path. Instead of waiting for a human to manually test the sequence, they instruct their agent to run trigger_webhook with a test payload. The agent confirms the workflow started correctly, validating the flow without manual clicks.
Updating user info during a chat
A user tells the chatbot they moved or changed their phone number. The agent catches this data, then runs update_user with the new data. This immediately syncs the user's profile record without the user having to leave the chat interface.
Disabling a buggy flow instantly
A newly launched chatbot feature starts failing and spamming users. The agent detects this and runs list_workflows to find the faulty flow, then uses toggle_workflow to disable it immediately. The problem is contained in seconds.
The Tradeoffs
Trying to manage flows through the GUI
Logging into the Flow XO dashboard, navigating to 'Workflows', finding the flow, and toggling the switch. This takes multiple clicks and is only available through the web interface.
→
Use the list_workflows tool to confirm the flow name, then execute toggle_workflow directly through your AI agent. This is faster, repeatable, and works regardless of your current browser window.
Forgetting to check user status
Sending a critical follow-up message to a user who might have deleted their account or changed their platform. The message fails, and you have no record of why.
→
Always call get_user_details first. This confirms the user exists and provides the necessary context before you try to send a message with send_push_message.
Over-relying on manual data entry
A specialist needs to update a user's tier level, but instead of using the API, they manually open the user record and type in the new data. This is slow and error-prone.
→
Use the update_user tool. Provide the user ID and the new metadata. This guarantees the change is applied correctly and is logged via the agent's execution history.
When It Fits, When It Doesn't
Use this server if your core need is managing chatbot backend actions—user records, workflow status, or communication—from a chat interface. You should use it if you need to audit a user's history (list_user_history), trigger a manual test sequence (trigger_webhook), or change a user's data (update_user).
Don't use this if you just need to read simple, static data that isn't connected to a user or workflow. For example, if you only need a list of countries, don't use list_bot_accounts. Use a specialized, non-connected data source instead. If you only need to know if a workflow exists, use list_workflows, but if you need to change its status, you must use toggle_workflow.
Always remember the distinction: list_workflows just reads the names; toggle_workflow actually changes the state.
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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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 12 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Manual chatbot management requires jumping between dashboards and tabs.
Today, if a user asks about their account, you copy their ID, then open the user management dashboard. You have to navigate to the history tab, find the conversation thread, and then copy the ID again to send a follow-up message. This is three separate actions, three different screens, and a lot of copy-pasting.
With the Flow XO MCP Server, you tell your agent: 'Check user XYZ's history, then send a follow-up message.' The agent executes `get_user_details`, runs `list_user_history`, and finally uses `send_push_message`. You get the full result, end-to-end, without ever leaving your chat window.
Send and control workflows with Flow XO MCP Server
Manually triggering a workflow means going into the Flow XO UI, selecting the flow, and hitting the 'Test' button. This is slow, and you often have to manually feed test data into the payload box to simulate the trigger. It's a clunky, multi-step process.
Now, your agent handles it. You just tell it to `trigger_webhook` and provide the necessary data. The agent executes the payload push, starting the automation immediately. It's direct, verifiable, and works whether or not the UI is open.
Common Questions About Flow XO MCP
How do I check if a chatbot workflow is running using `list_workflows`? +
The list_workflows tool lists all defined flows and their names. To check if it's active, you must then use toggle_workflow and confirm its current status, or check the overall system analytics with get_automation_analytics.
What data do I need to send to `send_push_message`? +
You need the unique user identifier and the specific response path. The agent uses these parameters to deliver the message, ensuring it lands in the correct spot for the user.
Can I update user data using `update_user`? +
Yes. You provide the user ID and the specific metadata fields (e.g., phone_number, email) you want to change. The tool executes the update and confirms the change.
Is `list_user_history` better than checking the chat log manually? +
Yes. list_user_history pulls the structured, complete message log directly through the API. This is better because it's guaranteed to be the full, authoritative record, not just what's displayed on the screen.
How do I list all users using `list_chatbot_users`? +
You call list_chatbot_users with no parameters. The agent returns a list of all active user IDs and their basic metadata, which you can then use for further actions.
How do I check if a user exists before trying to update them using `get_user_details`? +
First, run get_user_details with the user's ID. This confirms the user's existence and fetches their current profile data. You can then use update_user with the retrieved data to modify their metadata.
What data do I need to trigger a sequence using `trigger_webhook`? +
You must provide the specific webhook URL and the JSON payload required by the Flow XO endpoint. The payload structure depends entirely on what the target automation is designed to receive.
Can I see all the connected channels and platforms using `list_bot_accounts`? +
Yes, list_bot_accounts lists every connected platform (like Slack or Messenger) and the associated bot accounts. This helps you confirm the full scope of your bot's connectivity.
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.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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