How to Use the Galxe MCP in Vercel AI SDK

Q: How do I connect the Galxe MCP server to the Vercel AI SDK?

Install @ai-sdk/mcp and define your HTTP transport URL. Pass the endpoint into createMCPClient and grab the tools using mcpClient.tools(). Feed those directly into streamText to start rendering.

Q: Can the Vercel AI SDK stream Galxe quest data in real-time?

Yes. The SDK takes the raw JSON from getquest and streams the generated text to your React or Svelte frontend. Users watch the campaign rules populate instantly.

Q: What happens when a Galxe credential check fails in the Vercel AI SDK?

The LLM receives the negative response from checkcredentialeligibility and immediately generates fallback text. Your UI renders this rejection message live, prompting the user to complete the missing tasks.

Q: How do I manage API credentials programmatically?

You trigger the mutatecredentialitems tool. This allows your agent to add or remove eligible users from an API credential based on custom logic you define in your application.

Stream live Galxe leaderboard rankings and quest eligibility straight into your Next.js frontend using the Vercel AI SDK.

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Connect Galxe MCP to Vercel AI SDK

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

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Live Vercel AI SDK Quest Streams

Your agent pulls live campaign data using `get_quest` and streams the exact requirements directly into the UI. Users see the campaign parameters appear instantly, skipping the usual loading spinners entirely. You feed the Vercel AI SDK the MCP Server endpoint and pass the tools to `streamText`. The frontend renders the quest details block by block as the LLM processes the response.

Instant Credential Checks

The `check_credential_eligibility` tool queries the Galxe backend to verify a specific wallet address against your campaign requirements. You run this check mid-conversation and display the result the moment the data hits the client. Building loyalty dashboards requires immediate feedback. When a user asks if they qualify, the system executes `check_quest_eligibility` behind the scenes and updates their status on screen without a page refresh.

Render Live Leaderboards

Fetch real-time loyalty points by triggering `get_space_leaderboard` during a chat session. The AI processes the top-ranked accounts and formats them into a clean React component on the fly. This MCP Server also includes `get_starboard_leaderboard` for tracking Twitter influence scores. You pipe that data through the SDK to show users exactly where they stand in the community hierarchy.

Setup guide

Set up Galxe 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 Galxe 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 Galxe transactions",
});

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Galxe. 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 Galxe MCP in Vercel AI SDK

Install `@ai-sdk/mcp` and define your HTTP transport URL. Pass the endpoint into `createMCPClient` and grab the tools using `mcpClient.tools()`. Feed those directly into `streamText` to start rendering.

Yes. The SDK takes the raw JSON from `get_quest` and streams the generated text to your React or Svelte frontend. Users watch the campaign rules populate instantly.

The LLM receives the negative response from `check_credential_eligibility` and immediately generates fallback text. Your UI renders this rejection message live, prompting the user to complete the missing tasks.

You trigger the `mutate_credential_items` tool. This allows your agent to add or remove eligible users from an API credential based on custom logic you define in your application.

The V8 Isolate Sandbox processes Web3 wallet addresses and Twitter handles in a purely ephemeral state. Vinkius drops the container the moment the request finishes, leaving zero trace of your users' identity data.

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