How to Use the DappRadar (Web3 Dapp & NFT Analytics) MCP in Vercel AI SDK

Q: How do I hook up the DappRadar (Web3 Dapp & NFT Analytics) MCP Server to my Vercel AI SDK application?

Install @ai-sdk/mcp and create an HTTP client pointing to your Vinkius endpoint. Pass the tools array from mcpClient.tools() into your streamText call, then close the client connection when the request finishes.

Q: Can I use DappRadar (Web3 Dapp & NFT Analytics) to build real-time charts in Vercel AI SDK?

Yes. You call getdappmetrics or getnftcollectionmetrics to get raw data points. The SDK streams this structured data directly to your frontend components, allowing you to update charts live.

Stream Web3 dapp metrics and NFT collection stats directly into your Next.js frontend using the Vercel AI SDK.

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Connect DappRadar (Web3 Dapp & NFT Analytics) MCP to Vercel AI SDK

Create your Vinkius account to connect DappRadar (Web3 Dapp & NFT Analytics) 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 DappRadar (Web3 Dapp & NFT Analytics) with Vercel AI SDK

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Stream live chain stats to your UI

The `get_chain_stats` tool pulls real-time blockchain ecosystem metrics directly into your Vercel AI SDK stream. Your users see active wallets, transaction counts, and volume updates appear on their screens without waiting for a full page reload. By passing this tool to `streamText`, your Next.js app handles the raw data transfer in the background. It renders the incoming JSON into clean UI components as soon as the blockchain data resolves.

Pull historical dapp metrics instantly

The `get_dapp_metrics` tool pulls historical activity data for any decentralized application on the DappRadar registry. Your AI client reads these metrics to analyze user retention or transaction volume trends over custom timeframes. Combining this with the Vercel AI SDK allows your frontend to render real-time charts. You avoid complex backend state management by letting the SDK pipe the raw data directly to your chart components.

Build an interactive NFT explorer with this MCP Server

The `get_nft_collection_metrics` tool extracts historical floor prices, volumes, and sales counts for any supported NFT contract. Chat sessions query this data to give users instant market insights in real time. This MCP Server integration runs inside Edge Functions, keeping your API overhead low. Your users get fast, low-latency responses because the connection bypasses heavy cold starts.

Setup guide

Set up DappRadar (Web3 Dapp & NFT Analytics) 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 DappRadar (Web3 Dapp & NFT Analytics) 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 DappRadar (Web3 Dapp & NFT Analytics) 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 DappRadar. 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 DappRadar (Web3 Dapp & NFT Analytics) MCP in Vercel AI SDK

Install `@ai-sdk/mcp` and create an HTTP client pointing to your Vinkius endpoint. Pass the tools array from `mcpClient.tools()` into your `streamText` call, then close the client connection when the request finishes.

Yes. You call `get_dapp_metrics` or `get_nft_collection_metrics` to get raw data points. The SDK streams this structured data directly to your frontend components, allowing you to update charts live.

You configure your agent to pass limit and offset parameters to `list_dapps`. The SDK parses the paginated response, enabling your UI to render the next set of dapps dynamically.

Yes, the HTTP transport for this setup is fully compatible with Edge Functions. You can fetch and stream Web3 data without worrying about Node.js-only library dependencies.

Vinkius runs the server in a zero-trust, ephemeral sandbox where your secret tokens never expose themselves to the browser. Only the structured metrics like transaction volumes and NFT prices flow to your frontend.

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