How to Use the Finmei MCP in Mastra AI

Q: Can I require human approval before Mastra AI deletes a payment in Finmei?

Yes. You can configure Mastra's approval flag on the deletepayment tool. The agent will pause and wait for a manual confirmation before removing the payment record.

Q: How do I sync expense categories between Finmei and Mastra AI workflows?

Your Mastra agent calls listcategories to fetch the current active categories. It then matches these categories against incoming receipts before calling createexpense to ensure consistent ledger mapping.

Q: Can Mastra AI run complex branching logic based on expense amounts?

Yes. Mastra can query getexpense and branch its workflow based on the amount. For example, expenses over a certain threshold can trigger an approval chain, while smaller amounts are automatically reconciled on the MCP Server.

Q: How does Mastra AI secure my business profile and payment details?

Access to getprofile and getpayment is managed through Vinkius's secure sandbox. Mastra connects via a single endpoint token under the hood of this MCP setup, keeping your banking and corporate data completely isolated from external threats.

Build resilient, multi-step expense workflows with Mastra AI and the Finmei MCP Server.

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Autonomous expense validation loops with Mastra AI

The `get_expense` tool fetches detailed ledger entries to initiate Mastra AI's validation workflows. Your agent uses this data to cross-reference transactions against your company policies before committing them to the ledger. If the transaction looks suspicious, the Mastra workflow triggers `delete_expense` to reject the entry. This automated loop ensures that only pre-approved, valid transactions remain in your active database using this MCP integration.

Multi-step payment retries with Mastra AI

The `list_payments` tool monitors outstanding balances to trigger automated payment runs. When a payment fails, Mastra's workflow engine catches the error and retries the transaction using alternative currencies found via `list_currencies`. Once the payment succeeds, the workflow calls `get_payment` to verify the transaction details. It then updates the original ledger entry using `update_expense` to mark the transaction as fully settled.

Human-in-the-loop tax rate approvals

The `list_tax_types` tool retrieves tax categories that require verification before application. Mastra AI uses its built-in approval engine to pause the workflow and request human sign-off before applying a new tax rate to an expense using this MCP setup. Once approved, the agent executes `create_expense` with the verified tax rate. This prevents tax classification mistakes from corrupting your financial records.

Setup guide

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

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

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

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Common questions about Finmei MCP in Mastra AI

Mastra uses its built-in retry engine with exponential backoff. If `create_expense` fails due to a network glitch, the workflow automatically retries the call before alerting your team.

Yes. You can configure Mastra's approval flag on the `delete_payment` tool. The agent will pause and wait for a manual confirmation before removing the payment record.

Your Mastra agent calls `list_categories` to fetch the current active categories. It then matches these categories against incoming receipts before calling `create_expense` to ensure consistent ledger mapping.

Yes. Mastra can query `get_expense` and branch its workflow based on the amount. For example, expenses over a certain threshold can trigger an approval chain, while smaller amounts are automatically reconciled on the MCP Server.

Access to `get_profile` and `get_payment` is managed through Vinkius's secure sandbox. Mastra connects via a single endpoint token under the hood of this MCP setup, keeping your banking and corporate data completely isolated from external threats.

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