How to Use the Flow XO MCP in Mastra AI

Q: Is it possible to track Flow XO user history in Mastra AI?

You use listuserhistory to pull recent logs. The agent then analyzes these logs to decide on the next step in the workflow.

Q: What data privacy measures protect my Flow XO users in Mastra AI?

The server restricts access to listchatbotusers based on your provided token. Only authorized agents can query or modify individual user records.

Build resilient multi-step workflows in Mastra AI. Manage bot logic and user interactions with automated retry and error handling.

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Connect Flow XO MCP to Mastra AI

Create your Vinkius account to connect Flow XO to Mastra AI 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 Mastra AI

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Perplexity

Conditional automation control for Mastra AI

Create complex branching logic by calling `toggle_workflow` based on your agent's internal state. If a condition fails, you can disable the flow immediately. This gives your agents control over the automation environment. You define the rules, and the server executes them exactly as instructed.

Granular user management in Mastra AI agents

Update user metadata or look up profiles using `update_user` and `get_user_details`. Your agents stay informed about who they are talking to. This keeps your agent memory accurate. You avoid stale data by querying the source of truth whenever the agent needs a context update.

Automated messaging sequences for agents

Use `send_push_message` to push updates during a multi-step workflow execution. Your agents can reach out to users at the right moment. It handles the outbound communication while your agent manages the logic. You get a clear separation of concerns between agent reasoning and external actions.

Setup guide

Set up Flow XO MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All Flow XO tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "flow-xo-mcp-client",
  servers: {
    "flow-xo-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Flow XO Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Flow XO tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Flow XO transactions"
);
console.log(result.text);

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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.

Why Choose Vinkius

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Common questions about Flow XO MCP in Mastra AI

You register the server in your agent config. Mastra then exposes the tools like `list_workflows` directly to your agent's reasoning engine.

Yes. The agent can trigger multiple webhooks or updates concurrently. You just need to ensure your API rate limits support the volume.

You use `list_user_history` to pull recent logs. The agent then analyzes these logs to decide on the next step in the workflow.

The agent receives an error response. You can implement retry logic in your agent workflow to handle the failure gracefully.

The server restricts access to `list_chatbot_users` based on your provided token. Only authorized agents can query or modify individual user records.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript

Mastra AI sdk-typescript

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