How to Use the Levo.ai (API Security & Observability) MCP in Vercel AI SDK

Stream real-time API security data directly into your interface with the Levo.ai (API Security & Observability) MCP Server for AI SDK.

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Connect Levo.ai (API Security & Observability) MCP to Vercel AI SDK

Create your Vinkius account to connect Levo.ai (API Security & Observability) 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 Levo.ai (API Security & Observability) with Vercel AI SDK

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Claude

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Real-time endpoint discovery in AI SDK

Visualize your entire API surface area by calling `list_catalog_endpoints`. You get a live feed of REST, GraphQL, and gRPC routes that your agent can process immediately. Stop guessing what services exist in your stack. This tool maps every shadow and zombie API, allowing your frontend to render active documentation as the agent finds it.

Stream vulnerability diagnostics

Feed security findings straight into your UI components using `list_vulnerabilities`. Your app displays active OWASP threats as they appear in the staging environment. Use `get_vulnerability` to pull detailed exploitation evidence for specific alerts. You don't wait for a background process; the data hits your state object the moment the agent retrieves it.

Monitor sensitive data flows

Identify where PII or PHI moves through your architecture by querying `list_sensitive_data`. Your agent flags these flows while the user watches the results stream into the browser. Check specific schema structures with `get_endpoint_details` to verify if sensitive fields are exposed. It turns abstract security logs into concrete UI elements your users can actually read.

Setup guide

Set up Levo.ai (API Security & Observability) 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 Levo.ai (API Security & Observability) 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 Levo.ai (API Security & Observability) transactions",
});

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Levo.ai. 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.

Why Choose Vinkius

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Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

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Single dashboard

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place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Levo.ai (API Security & Observability) MCP in Vercel AI SDK

Install the MCP client and point it at your Vinkius endpoint. You then pass the tools directly into your `generateText` call to start auditing your API catalog.

Yes. You map user prompts to tool calls, letting the agent decide when to run `list_observations` or `get_endpoint_details` based on the request context.

It is. The lightweight transport allows your edge functions to query the MCP server without adding significant latency to your request cycle.

Vinkius handles the underlying handshake. You provide your endpoint token once, and the client maintains the connection while you focus on building the UI.

The server only touches your API metadata and schema structures. It does not store your actual production traffic payloads, focusing strictly on endpoint diagnostics and vulnerability logs.

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