How to Use the Feathery MCP in Mastra AI

Q: How do I register the Feathery MCP Server with my Mastra AI agent?

Instantiate the MCPClient from @mastra/mcp with your Vinkius URL. Then, call listTools() on that client and spread them directly into your agent's tool configuration array.

Q: Can Mastra AI handle human-in-the-loop approvals for Feathery actions?

Yes, you can set requireToolApproval on your Mastra agent before it runs tools like listconnectorlogs. This ensures a human reviews any system diagnostic actions before they execute.

Q: How does Mastra AI manage conditional branching based on Feathery forms?

The agent calls getformdetails to read the form schema, then uses Mastra's workflow engine to route users. For example, if a user selects 'Enterprise', the workflow branches to a high-priority sales queue.

Build self-healing form automation workflows using Mastra AI and Feathery tools with automatic retries.

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Connect Feathery MCP to Mastra AI

Create your Vinkius account to connect Feathery 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 Feathery with Mastra AI

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Automating Forms with Mastra AI and the Feathery MCP Server

The `get_workflow_details` tool retrieves the structure and status of your active automation pipelines. Mastra AI uses this structure to execute conditional logic, routing users to different steps based on their previous form answers. If a step fails, Mastra's built-in retry engine uses `list_workflows` to check alternative paths. This keeps your business operations running without manual developer intervention.

Automated Webhook Monitoring

The `list_connector_logs` tool identifies failures in your external database integrations and third-party webhooks. Mastra AI monitors these logs and triggers automatic retries when it detects a temporary connection drop. By pairing this with `get_account_info` via the MCP Server, your agent can verify if an integration failure is due to account limitations or a temporary service outage. You get instant alerts with full context before your team notices.

Dynamic User State Sync

The `get_form_session` tool tracks the exact step a user abandoned on an active form. Mastra agents use this session data to trigger personalized email reminders or adjust CRM records. You also call `list_users` to match abandoned sessions with known email addresses in your system. This allows you to resume user journeys precisely where they left off.

Setup guide

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

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

const result = await agent.generate(
  "List recent Feathery 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 Feathery. 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 Feathery MCP in Mastra AI

Instantiate the `MCPClient` from `@mastra/mcp` with your Vinkius URL. Then, call `listTools()` on that client and spread them directly into your agent's tool configuration array.

Yes, you can set `requireToolApproval` on your Mastra agent before it runs tools like `list_connector_logs`. This ensures a human reviews any system diagnostic actions before they execute.

The agent calls `get_form_details` to read the form schema, then uses Mastra's workflow engine to route users. For example, if a user selects 'Enterprise', the workflow branches to a high-priority sales queue.

Mastra's workflow engine automatically retries failed calls to tools like `get_user_data` using exponential backoff. This prevents temporary network hiccups from breaking your data sync pipelines.

Yes, because your API keys and account details retrieved by `get_account_info` are never stored by Vinkius. All tool execution on this MCP Server occurs in isolated, ephemeral environments that destroy data immediately after the agent finishes its run.

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