How to Use the Legal Fees Apportionment Engine MCP in Mastra AI

Automate complex settlement workflows in Mastra AI with precise fee-splitting logic.

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Connect Legal Fees Apportionment Engine MCP to Mastra AI

Create your Vinkius account to connect Legal Fees Apportionment Engine 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 Legal Fees Apportionment Engine with Mastra AI

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Conditional fee logic for Mastra AI

Build agent workflows that use `apportion_legal_fees` to decide the next step in a settlement process. If the math hits a specific threshold, trigger your next agent automatically. This gives your agents the ability to handle complex billing logic as part of a larger chain. No more manual intervention for standard fee distributions.

Automatic retries for settlement workflows

The Mastra AI framework handles the connection to this MCP Server with built-in resilience. If a calculation request fails, your workflow retries instantly. Your agents maintain state throughout the process. This ensures that every step of the fee apportionment remains consistent even if the network blips.

Human-in-the-loop approval for fee splits

Use the `apportion_legal_fees` tool with your agent's approval gate. The agent performs the math, but you hold the keys to authorize the final distribution. It keeps your operations transparent and secure. You get a clear audit trail of every decision made by your agents before any action is finalized.

Setup guide

Set up Legal Fees Apportionment Engine 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 Legal Fees Apportionment Engine 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: "legal-fees-apportionment-engine-mcp-client",
  servers: {
    "legal-fees-apportionment-engine-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

const result = await agent.generate(
  "List recent Legal Fees Apportionment Engine transactions"
);
console.log(result.text);

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Common questions about Legal Fees Apportionment Engine MCP in Mastra AI

Add the server URL to your Mastra client configuration. The `apportion_legal_fees` tool will immediately appear as an available action for your agents.

Yes. You can chain this tool with other agents to automate the entire lifecycle of a legal claim. It fits perfectly into multi-step workflows.

Yes, you can configure your agent to request human approval before executing any fee calculations. This adds an essential layer of oversight.

The engine is built for high-stakes environments. It provides deterministic outputs, which makes it ideal for automated financial workflows.

Your settlement data stays within your private memory space. The server operates in an ephemeral sandbox, ensuring no trace of your figures is left behind after the workflow finishes.

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