How to Use the Dextools (DeFi Token Data API) MCP in Vercel AI SDK

Q: How do I connect the Dextools (DeFi Token Data API) MCP Server to my Vercel AI SDK project?

Install @ai-sdk/mcp and ai via npm, then set up the server client using createMCPClient with your HTTP endpoint. You pass the tools directly into generateText or streamText to let your agent fetch live token metrics.

Q: Can I stream Dextools (DeFi Token Data API) price updates in real-time using Vercel AI SDK?

Yes. When your agent calls gettokenprice, the Vercel AI SDK streams the resulting tool execution output directly to your React or Next.js frontend, letting users see the price updates as they happen.

Fetch live token metrics directly into your Vercel AI SDK stream without UI blocking.

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Connect Dextools (DeFi Token Data API) MCP to Vercel AI SDK

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Setup Dextools (DeFi Token Data API) with Vercel AI SDK

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Live Token Pricing in Your Vercel AI SDK Chat UI

The `get_token_price` tool fetches live USD rates for any token address on supported networks. Your AI client pulls this number and streams it directly to the user's browser, bypassing the usual loading spinners that ruin modern web apps. By passing this tool to your Vercel AI SDK `streamText` function, you render live token valuations in React or Next.js components instantly. This means your users get instant financial updates while the conversation is still streaming.

Instant Liquidity Analysis via MCP Server Tools

The `get_token_liquidity` tool extracts total locked value and pool depth for any given pair. Your application takes this raw metric and feeds it into the model context to assess market slippage on the fly. You use this data to build interfaces that warn traders before they execute high-slippage swaps. The model processes the raw liquidity figures alongside the chat context, rendering custom warnings directly in the user's interactive UI.

Multi-Chain Pair Verification and Metadata Retrieval

The `get_pair` and `get_blockchains` tools identify active trading pools across dozens of EVM and non-EVM networks. Your front-end client uses these endpoints to verify that a token contract actually has active trading pairs before attempting to fetch its price. Integrating these tools with the Vercel AI SDK lets your agent verify contract addresses across different chains on demand. This stops users from querying dead contracts or inputting fake token addresses into your interface.

Setup guide

Set up Dextools (DeFi Token Data API) 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 Dextools (DeFi Token Data API) 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 Dextools (DeFi Token Data API) transactions",
});

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

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Common questions about Dextools (DeFi Token Data API) MCP in Vercel AI SDK

Install `@ai-sdk/mcp` and `ai` via npm, then set up the server client using `createMCPClient` with your HTTP endpoint. You pass the tools directly into `generateText` or `streamText` to let your agent fetch live token metrics.

Yes. When your agent calls `get_token_price`, the Vercel AI SDK streams the resulting tool execution output directly to your React or Next.js frontend, letting users see the price updates as they happen.

You must manage rate limits at the application layer or within your MCP client configuration. If Dextools returns a rate limit error, the SDK receives that error as a tool execution failure, which your UI can gracefully display to the user.

No. The tool output returns structured JSON directly to the SDK, which your agent processes automatically without manual parsing.

Your token contract addresses and chain queries route directly through the Vinkius sandbox to the Dextools API. No wallet private keys or transaction data are ever touched, as the server only queries public on-chain liquidity and pricing metadata.

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