How to Use the Degreed MCP in Vercel AI SDK

Q: How do I search the Degreed catalog using the Vercel AI SDK?

Your agent uses the searchlearningcatalog tool. Pass a search term to it, and the Vercel AI SDK will stream the matching course and content results directly into your UI components.

Q: Can I build a UI that shows a user's Degreed learning history?

Yes. The listusercompletions tool is designed for this. It returns a history of all completed learning items for a specific user, which you can then render in your application.

Q: What's the best way to list our company's skills from Degreed with the Vercel AI SDK?

Use the listdefinedskills tool. It returns your organization's official skill taxonomy from Degreed. You can then stream this data into a filterable list or a set of tags in your UI.

Q: How does this MCP Server connect to my Vercel project?

You install the @ai-sdk/mcp package and use createMCPClient with the secure URL provided by Vinkius. Then you pass the tools from the client to the generateText or streamText functions.

Stream Degreed learning data directly into your app with the Vercel AI SDK. No loading spinners, just live results.

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Connect Degreed MCP to Vercel AI SDK

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

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Build a Live Learning Search UI

Stop making users wait for a search page to load. With the Vercel AI SDK, you can build a search box that streams results as the user types. Your agent calls `search_learning_catalog`, and the UI populates with course titles and links in real time. Then, when a user clicks a result, you can instantly fetch and display its metadata. Use `get_content_details` to pull the full description, duration, and associated skills. The data appears on the screen as it arrives, which makes your app feel incredibly responsive.

Create Real-time Skill Dashboards

Build a manager dashboard that shows a live view of your team's skills. Your agent can call `get_user_profile` and `list_user_completions` for each team member. Instead of a static report, the data streams directly into your React or Next.js components. As the information flows in, charts and progress bars update on the fly. A manager can see who just finished a course or which skills are trending up, right as it happens. It turns a boring data table into a live pulse of team development.

Interactive Onboarding with this MCP Server

You can use this Degreed MCP server to design a better onboarding experience. First, your agent fetches an onboarding sequence using `list_learning_pathways`. The Vercel AI SDK then streams the steps into your UI, showing the new hire exactly what's next. When they complete a course, the interface can immediately query `list_user_completions` to confirm it. The UI checks off the item and shows their progress. This makes corporate training feel less like a checklist and more like an interactive guide.

Setup guide

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

Your agent uses the `search_learning_catalog` tool. Pass a search term to it, and the Vercel AI SDK will stream the matching course and content results directly into your UI components.

Yes. The `list_user_completions` tool is designed for this. It returns a history of all completed learning items for a specific user, which you can then render in your application.

Use the `list_defined_skills` tool. It returns your organization's official skill taxonomy from Degreed. You can then stream this data into a filterable list or a set of tags in your UI.

You install the `@ai-sdk/mcp` package and use `createMCPClient` with the secure URL provided by Vinkius. Then you pass the tools from the client to the `generateText` or `streamText` functions.

This server accesses Degreed user profiles, skill ratings, and learning completion histories. Your Vercel AI SDK client connects using a single Vinkius endpoint token, and all operations run inside an ephemeral, zero-trust sandbox for each request.

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