How to Use the ZenHub MCP in Vercel AI SDK

Q: How can I get ZenHub board status using the Vercel AI SDK?

You invoke getrepoboard through your agent. The data for the board streams into your UI, so users watch the project structure materialize in real time. This makes the experience feel incredibly snappy.

Q: Does the Vercel AI SDK handle ZenHub issue metadata?

Yes. You can use getzenhubissuedata to retrieve specific, ZenHub-only details attached to a GitHub issue. This data streams right into your client, allowing you to display custom fields instantly.

Q: What if I need to move an issue using the Vercel AI SDK?

You call moveissuebetweenpipelines directly from your agent. It handles moving the issue ID to a new pipeline, and because it’s streamed, you get confirmation of the change immediately.

Q: Can I list ZenHub epics using the Vercel AI SDK?

Absolutely. The listrepoepics tool lets your agent fetch all epics for a given repository. You then stream this list into your UI, providing project context instantly.

Stream real-time agile data into your UI with the Vercel AI SDK.

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Connect ZenHub MCP to Vercel AI SDK

Create your Vinkius account to connect ZenHub 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 ZenHub with Vercel AI SDK

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Get Epic Details for Your App

Need to show a user the full scope of an epic? Call `get_epic_data` to grab specific details about any given ZenHub epic. You pass in an ID, and the data streams back instantly, letting your agent display the information as it arrives. This makes building dynamic dashboards simple. Instead of dumping all the info at once, you stream it out piece by piece into React or Next.js.

Manage Repository Boards Live

Check a repo's entire status using `get_repo_board`. Your agent fetches the board layout for any repository and streams that data directly to your frontend. The user sees the structure appear in real-time, making it feel like they’re interacting with the live system. It's perfect for components that need immediate feedback on project status without waiting for a full page refresh.

Adjust Issue Estimates Fast

Setting story points shouldn't be clunky. Use `set_issue_estimate` to let your agent update the effort estimate right from the chat window. The function takes an issue ID and a new point value, executing the change instantly. This capability lets users interact with project management tasks naturally. Your AI client handles the API call, and you display success or failure immediately.

Setup guide

Set up ZenHub 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 ZenHub 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 ZenHub 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 ZenHub. 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 ZenHub MCP in Vercel AI SDK

You invoke `get_repo_board` through your agent. The data for the board streams into your UI, so users watch the project structure materialize in real time. This makes the experience feel incredibly snappy.

Yes. You can use `get_zenhub_issue_data` to retrieve specific, ZenHub-only details attached to a GitHub issue. This data streams right into your client, allowing you to display custom fields instantly.

You call `move_issue_between_pipelines` directly from your agent. It handles moving the issue ID to a new pipeline, and because it’s streamed, you get confirmation of the change immediately.

Absolutely. The `list_repo_epics` tool lets your agent fetch all epics for a given repository. You then stream this list into your UI, providing project context instantly.

This server handles issue estimates and general agile board metadata. Specifically, it manages story point estimates for issues and repository/workspace board configurations. Keep track of which fields are being written.

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