How to Use the Fee Navigator MCP in Mastra AI

Q: How do I handle failed statement uploads in Mastra AI using Fee Navigator?

You wrap the uploadstatement tool in a Mastra workflow block. If the server returns a rate limit, the workflow engine automatically retries the upload using exponential backoff.

Q: Can a Mastra AI agent automatically generate proposals with Fee Navigator?

Yes. You can build a multi-step agent that triggers analyzestatement on a new file, waits for the result, and then calls getproposal to compile the savings breakdown.

Run automated, self-healing merchant statement audits with Mastra AI and the Fee Navigator MCP Server.

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Connect Fee Navigator MCP to Mastra AI

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Setup Fee Navigator with Mastra AI

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Automated Multi-Step Audit Workflows

Stop writing manual glue code to handle failed statement uploads. With Mastra AI, you build workflows that automatically retry `upload_statement` if the connection drops. The system handles transient API errors silently in the background. Once the file is up, the workflow triggers `analyze_statement` to parse the fees. If the parser detects an unusual processor format, the agent branches to alert your team while logging the event.

Dynamic Fee Benchmarking with Mastra AI

Build agents that actively monitor merchant performance against industry averages. The Mastra engine schedules regular runs to fetch data using `get_industry_stats` and compares it with your active accounts. If a merchant's average markup exceeds the benchmark, the agent calls `list_proposals` to find better pricing options. This allows you to run background optimization tasks without manual supervision.

Resilient Merchant Account Syncing

Keeping your internal database in sync with your processing accounts is a headache. This MCP Server exposes `list_merchants` to let your Mastra agent poll for new additions. The agent verifies each account using `get_account_info` and logs the activity. If any step fails, Mastra's built-in backoff engine retries the call to prevent data gaps.

Setup guide

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

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

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

You wrap the `upload_statement` tool in a Mastra workflow block. If the server returns a rate limit, the workflow engine automatically retries the upload using exponential backoff.

Yes. You can build a multi-step agent that triggers `analyze_statement` on a new file, waits for the result, and then calls `get_proposal` to compile the savings breakdown.

You register the server URL in your Mastra client configuration. The framework auto-discovers all 12 tools, including `list_recent_activities`, making them immediately available to your agents.

Yes. Mastra supports human-in-the-loop approvals, meaning your agent can pause after `get_audit` and wait for a manager to approve the proposal before sending it to the client.

Your merchant fee profiles and statement PDFs are processed within isolated V8 sandboxes using this MCP setup. The transmission of transaction volume data and merchant IDs is protected by end-to-end TLS encryption, ensuring no raw financial data leaks.

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