How to Use the LinearB MCP in Vercel AI SDK

Q: How do I fetch LinearB metrics in Vercel AI SDK?

Initialize the MCP client via the HTTP transport and call querysoftwaremetrics within your streamText function. You define the specific metrics and time ranges in the tool body.

Stream real-time engineering metrics directly into your Vercel AI SDK interface for instant visibility into your delivery pipeline.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect LinearB MCP to Vercel AI SDK

Create your Vinkius account to connect LinearB 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.

GDPR Free for Subscribers

Setup LinearB with Vercel AI SDK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Live deployment and incident tracking

Feed your dashboard real-time data by using `record_new_deployment` and `record_new_incident` directly within your edge functions. Your interface updates the moment an event hits the LinearB API, removing the delay of polling or manual status checks. Since this runs on the Vercel AI SDK, the results stream into your UI as they arrive. Developers see exactly what is happening in the repo without leaving the application window.

Engineering team visibility for your app

Call `list_engineering_teams` and `list_connected_repos` to map your organization structure inside your client-side tools. This allows you to build custom views that filter data based on specific teams or active project repositories. Your users get a clear picture of their environment. By combining these with `query_software_metrics`, you can render charts that show exactly how specific teams are performing against their current delivery goals.

Metrics-driven UI components

The LinearB MCP server lets you pull raw DORA data through `query_software_metrics` and pass it straight into your frontend components. You can visualize MTTR or deployment frequency without writing a custom backend layer. This keeps your code clean and your data fresh. Because the MCP server handles the API authentication, your Vercel AI SDK project stays lightweight and focused on the user experience.

Setup guide

Set up LinearB 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 LinearB 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 LinearB 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 LinearB. 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

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect LinearB now

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

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

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

Common questions about LinearB MCP in Vercel AI SDK

Initialize the MCP client via the HTTP transport and call `query_software_metrics` within your streamText function. You define the specific metrics and time ranges in the tool body.

Yes. The SDK catches tool execution failures, allowing you to log incidents using `record_new_incident` if a deployment script fails. This provides a closed loop for your automated workflows.

Your API credentials stay on the server side. The MCP server acts as the secure bridge, ensuring sensitive repository data is only accessed through authorized tool calls.

It provides the tools to report events as they happen. You trigger the reporting functions, and the state updates in your connected LinearB environment immediately.

The data resides in your existing LinearB account. Your AI client only requests information through the MCP protocol, so no persistent copies are stored in your frontend application.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript