How to Use the Datalastic Maritime MCP in Mastra AI

Q: Can Mastra AI handle conditional branching based on Datalastic Maritime coordinates?

Yes, you write workflows that inspect the output of getvesselstatus and take different paths. For example, if a ship is outside its expected zone, the workflow triggers findvesselsinradius.

Q: Does Mastra AI support human approval before fetching vessel history?

Yes, you flag getvesselhistory as requiring manual approval in your Mastra MCP tool configuration. The workflow halts and alerts your operator before pulling the tracking coordinates.

Build resilient maritime workflows that automatically retry vessel tracking and port lookups using Mastra AI.

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Connect Datalastic Maritime MCP to Mastra AI

Create your Vinkius account to connect Datalastic Maritime 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 Datalastic Maritime with Mastra AI

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Resilient Fleet Tracking Workflows

Shipping routes are unpredictable, and API calls to track them shouldn't fail silently. Mastra AI uses its workflow engine to run `get_vessel_status` and handle temporary network dropouts. This MCP Server setup ensures your tracking keeps running. If a vessel moves out of bounds, the workflow triggers `find_vessels_in_radius` to locate nearby alternatives. This ensures your automated tracking systems keep running even when specific vessel telemetry is temporarily spotty.

Automated Port Audits via Mastra AI Workflows

Auditing port entries requires matching vessel names with local harbor details. The MCP agent uses `search_maritime_vessels` to identify the ship, then branches conditionally based on its current destination. If the ship is headed to an unknown dock, Mastra AI triggers `search_ports_by_country` followed by `get_port_details` to verify the destination coordinates. You define these steps in code, and the engine executes them sequentially.

Human-in-the-Loop Approvals for Vessel History

Pulling deep AIS tracking logs consumes significant API quotas. By using Mastra AI's tool approval mechanism, you pause the agent before it calls `get_vessel_history` to get a human sign-off on the query. While waiting for approval, the agent still runs lightweight queries like `search_ports_by_name` to gather context. Once approved, the MCP client resumes and fetches the historical coordinates.

Setup guide

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

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

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

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Common questions about Datalastic Maritime MCP in Mastra AI

You register the MCP Server URL in your Mastra client configuration. The framework automatically discovers tools like `get_vessel_status` and exposes them to your agent's toolbelt.

Yes, you write workflows that inspect the output of `get_vessel_status` and take different paths. For example, if a ship is outside its expected zone, the workflow triggers `find_vessels_in_radius`.

Mastra's built-in queue system handles rate limits gracefully. If `get_vessel_pro_specs` hits a limit, the workflow engine retries the call automatically without crashing your application.

Yes, you flag `get_vessel_history` as requiring manual approval in your Mastra MCP tool configuration. The workflow halts and alerts your operator before pulling the tracking coordinates.

Telemetry data is processed in ephemeral memory inside an isolated V8 sandbox on Vinkius. No historical AIS records or vessel specifications are stored permanently on our servers.

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