How to Use the Accident Investigation Prover MCP in Vercel AI SDK

Stream accident investigation data directly into your Vercel AI SDK interface for real-time safety analysis and evidence correlation.

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Connect Accident Investigation Prover MCP to Vercel AI SDK

Create your Vinkius account to connect Accident Investigation Prover to Vercel AI SDK 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 Accident Investigation Prover with Vercel AI SDK

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Real-time evidence correlation with Vercel AI SDK

Feed FDR and CVR data into `validate_accident_investigation` to see how the model processes raw flight parameters against maintenance logs. Your UI updates instantly as the tool maps findings across the Swiss Cheese Model. Stop waiting for batch reports. By streaming these results, your app shows the exact moment the logic shifts from pilot action to organizational failure.

Structured ICAO Annex 13 analysis in your frontend

The `validate_accident_investigation` tool forces a rigorous multi-causal approach that prevents shallow conclusions. It breaks down complex HFACS levels into clear, actionable data points for your users. Your interface renders the causal chain directly. This keeps the investigation grounded in hard evidence rather than speculation.

Measurable safety outcomes for your users

Output specific, tracked recommendations instead of vague improvements. The tool ensures every safety directive is addressed to a specific authority and tied to a measurable metric. Your users get a clear view of the safety gaps. This turns raw investigation data into a concrete plan for preventing future incidents.

Setup guide

Set up Accident Investigation Prover MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all Accident Investigation Prover tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent Accident Investigation Prover transactions",
});

console.log(text);
await mcpClient.close();

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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 Accident Investigation Prover. 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 Accident Investigation Prover MCP in Vercel AI SDK

Install the MCP client package and initialize the connection using your endpoint URL. Pass the `validate_accident_investigation` tool into your generateText function to start processing logs.

Yes, the tool is designed for high-density FDR and CVR data. It processes these inputs efficiently to maintain performance within your streaming UI.

It replaces surface-level guesses with a strict HFACS taxonomy. This forces the model to identify systemic root causes instead of blaming the pilot.

The tool returns structured JSON that maps perfectly to your UI components. You can display causal chains, HFACS categories, and safety recommendations as live elements.

All flight telemetry and CVR transcripts remain ephemeral within the Vercel AI SDK session. We use zero-trust protocols to ensure your sensitive investigation data is never stored.

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