How to Use the Fieldfolio MCP in Mastra AI

Q: Does Mastra AI support Fieldfolio retries?

It does. You can configure the framework to retry updateinventory calls if the API encounters a temporary network issue.

Build reliable wholesale workflows with Fieldfolio and Mastra AI.

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Connect Fieldfolio MCP to Mastra AI

Create your Vinkius account to connect Fieldfolio 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 Fieldfolio with Mastra AI

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Automated order flows for Mastra AI

Chain `list_orders` and `get_order` within your Mastra agents to build multi-step processing logic. You can set up workflows that check order status and trigger follow-up actions automatically. If a step fails, the framework handles the retry logic for you. You define the path, and the agent executes the calls against your wholesale data.

Dynamic inventory control in Mastra AI

Sync your stock levels by integrating `list_inventory` with automated checks. If your agent detects a stock discrepancy, it uses `update_inventory` to correct the count immediately. This keeps your wholesale operations running without constant human oversight. The workflow engine ensures that every update is logged and verified.

Catalog automation via Mastra AI

Use `list_products` and `search_catalog` to build agents that assist warehouse staff in finding stock. The agent scans your entire catalog to answer questions about availability or category groupings. It handles the heavy lifting of catalog management. You spend less time searching and more time shipping orders.

Setup guide

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

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

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

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Common questions about Fieldfolio MCP in Mastra AI

Install the MCP client package and point it to your Fieldfolio server URL. The agent then auto-detects the tools and incorporates them into its toolset.

It does. You can configure the framework to retry `update_inventory` calls if the API encounters a temporary network issue.

You can. Use the tool filter during the agent setup to expose only the specific tools required for your current workflow.

You provide your endpoint token during server initialization. The client handles the secure handshake so your agent can act on your behalf.

Your data is private to your instance. The server only transmits the specific order details retrieved during an agent's execution loop.

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