How to Use the Highlight (Session Replay & UX) MCP in Vercel AI SDK

Q: Does the MCP Server pause while sending raw logs?

You can fire ingestrawlog asynchronously while the Vercel AI SDK continues streaming text to the user. The UI never blocks for telemetry.

Stream observability data directly into Highlight while your Vercel AI SDK app renders real-time UI updates.

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Connect Highlight (Session Replay & UX) MCP to Vercel AI SDK

Create your Vinkius account to connect Highlight (Session Replay & UX) 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 Highlight (Session Replay & UX) with Vercel AI SDK

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Stream OTLP Traces Live

Using the `ingest_otlp_traces` tool, your Vercel AI SDK app can push JSON trace data right as the edge function executes. This binds backend execution directly to the user's session replay. You do not have to guess why a generation timed out. Just watch the session and read the trace.

Vercel AI SDK MCP Server Logging

Firing off raw text logs straight to Highlight without setting up full OpenTelemetry is easy with the `ingest_raw_log` tool. It acts as an immediate escape hatch for edge debugging. Your agent encounters an unexpected state, ships the raw log, and you see it pop up in the console next to the session recording.

Structured OTLP Log Ingestion

Heavy-duty telemetry requires the `ingest_otlp_logs` tool to push standard OTLP JSON payloads from your Vercel AI SDK agents. Just remember to pack the `highlight.project_id` attribute into the payload or the server drops it. You get the flexibility of LLM-driven edge functions combined with the rigid structure of proper OTLP monitoring.

Setup guide

Set up Highlight (Session Replay & UX) 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 Highlight (Session Replay & UX) 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 Highlight (Session Replay & UX) transactions",
});

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

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Common questions about Highlight (Session Replay & UX) MCP in Vercel AI SDK

Run npm install ai @ai-sdk/mcp. Instantiate it using createMCPClient with an HTTP transport URL pointing to the MCP Server. Pass the resulting tools to your streamText function.

The HTTP transport works perfectly in edge environments. Your agent pushes traces and logs without relying on heavy Node.js dependencies.

You forgot the project ID. The payload must explicitly include the highlight.project_id attribute. Without it, the ingestion endpoint ignores the data.

You can fire ingest_raw_log asynchronously while the Vercel AI SDK continues streaming text to the user. The UI never blocks for telemetry.

Your AI client only touches OTLP logs, traces, and raw log strings. The V8 Isolate Sandbox keeps the execution environment completely ephemeral. Once the HTTP request finishes, the sandbox dies, leaving zero persistent connection to your internal network.

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