How to Use the Channable MCP in Mastra AI

Build resilient ecommerce workflows in Mastra AI that handle Channable order processing and stock management automatically.

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Connect Channable MCP to Mastra AI

Create your Vinkius account to connect Channable 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 Channable with Mastra AI

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Perplexity

Automate Channable tasks in Mastra AI

Chain multiple operations together to handle complex logic like retrying failed shipments. Use `list_order_shipments` to check status and then act accordingly. The workflow engine manages the execution flow. If an API call fails, Mastra AI handles the retry logic for you.

Conditional logic for marketplace returns

Create agents that look at `list_customer_returns` and decide whether to flag them for a human agent. You build the rules, the framework runs the check. This keeps your operations moving without manual intervention. The agent evaluates the return data and branches based on the result.

Scale stock management with Mastra AI

Deploy agents that watch for stock thresholds and run `update_product_stock` as needed. The framework ensures these tasks run reliably. You define the triggers and the agent handles the heavy lifting. It connects to your project to keep marketplace numbers synced.

Setup guide

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

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

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

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Common questions about Channable MCP in Mastra AI

Add the server URL to your agent configuration. The framework automatically detects the available tools for your workflow.

It will. You can configure exponential backoff directly within your workflow agent settings.

Absolutely. Use the requireToolApproval setting to pause the agent until you confirm the action.

You can pass project IDs to the tools dynamically. Your agent manages the context for each distinct project.

Your project and order data are processed in an ephemeral memory space. We ensure that shipment tracking numbers and customer details are scoped to your specific agent execution.

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