How to Use the HelloAsso MCP in Mastra AI

Q: How can I build a reliable payment notification workflow for HelloAsso with Mastra AI?

Create a Mastra AI workflow that periodically calls listpayments. For each new payment found, use the getpaymentdetails tool to get more info, and then use another tool (like a messaging service) to send a notification. Mastra's engine ensures this workflow runs reliably.

Q: Can a Mastra AI agent manage multiple HelloAsso organizations?

Yes. The agent's first step should be to use listmyorganizations to get the slugs for all accessible non-profits. Then, your workflow can loop through those slugs to perform actions like listorders or listsubscriptions for each one.

Q: Does this MCP integration for HelloAsso and Mastra AI handle different campaign types?

It does. The listforms tool returns all your campaigns, and each one has a formType field. Your Mastra AI workflow can use conditional logic to handle 'Donation', 'Membership', and 'Event' forms differently based on that value.

Q: How does Mastra AI connect to this HelloAsso server?

You install the @mastra/mcp package and point the client to the Vinkius URL for this server. Mastra handles the tool discovery and invocation, so you can focus on defining your workflow logic instead of messing with HTTP requests.

Build failure-proof workflows for HelloAsso with Mastra AI. Automate payment retries, notifications, and member management.

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Setup HelloAsso with Mastra AI

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Create Resilient Checkout Flows

Use the `create_checkout_intent` tool inside a Mastra AI workflow. If the API call to HelloAsso fails for some reason—a network hiccup, a temporary service outage—Mastra's engine automatically retries it with exponential backoff. You don't write that logic; it's just part of the framework. This means your agent's attempt to create a payment link is far more likely to succeed. Your workflow just proceeds to the next step once the link is ready, without you needing to code for every possible failure scenario.

Automate Member and Order Syncing

Chain together multiple HelloAsso tools to build a complete process. For example, create a workflow that runs `list_payments` on a schedule. For each new payment, use Mastra's conditional logic to trigger a call to `get_member_details` or `get_order_details`. If the payment is for a new membership, your workflow can add them to a welcome sequence. If an order contains a specific item from `list_sold_items`, it can trigger a fulfillment process. Mastra AI executes these multi-step operations reliably.

Human-in-the-Loop MCP Server Workflows

Some actions need a sanity check. With Mastra AI, you can build a workflow that requires human approval before proceeding. Your agent can use `list_my_organizations` to get context, prepare a summary of pending actions, and then pause. A team member gets a notification to approve or deny the batch operation. This gives you the automation of an MCP agent with the safety of manual review, which is critical for managing non-profit operations.

Setup guide

Set up HelloAsso 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 HelloAsso 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: "helloasso-mcp-client",
  servers: {
    "helloasso-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

const result = await agent.generate(
  "List recent HelloAsso 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 HelloAsso. 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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Common questions about HelloAsso MCP in Mastra AI

Create a Mastra AI workflow that periodically calls `list_payments`. For each new payment found, use the `get_payment_details` tool to get more info, and then use another tool (like a messaging service) to send a notification. Mastra's engine ensures this workflow runs reliably.

Yes. The agent's first step should be to use `list_my_organizations` to get the slugs for all accessible non-profits. Then, your workflow can loop through those slugs to perform actions like `list_orders` or `list_subscriptions` for each one.

It does. The `list_forms` tool returns all your campaigns, and each one has a `formType` field. Your Mastra AI workflow can use conditional logic to handle 'Donation', 'Membership', and 'Event' forms differently based on that value.

You install the `@mastra/mcp` package and point the client to the Vinkius URL for this server. Mastra handles the tool discovery and invocation, so you can focus on defining your workflow logic instead of messing with HTTP requests.

This MCP server acts as a pass-through proxy; it doesn't log or store your organization's data. When your Mastra AI agent calls a tool like `get_organization_details`, the request is authenticated, sent to HelloAsso, and the response is streamed back. The server environment is stateless.

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