How to Use the Acre Dados Abertos MCP in Vercel AI SDK

Q: How do I initialize the Acre Dados Abertos MCP Server with Vercel AI SDK?

Install @ai-sdk/mcp and ai, then use createMCPClient pointing to the Vinkius HTTP endpoint. Pass the tools to streamText and remember to call mcpClient.close() when the session ends to free up resources.

Q: Can I query specific Acre Dados Abertos tables using Vercel AI SDK tools?

Yes. Use searchdatastore to filter tabular records from the public registry. The SDK streams these rows directly to your React or Next.js frontend in real time.

Q: How does this MCP Server handle large dataset payloads in Edge Functions?

The server splits queries into manageable chunks. By using listpackages and getresource with streamText, your Edge Functions avoid timeout limits by flushing data to the client immediately.

Q: What is the cleanest way to display Acre thematic groups?

Call listgroups to fetch the high-level categories. Your agent can then map these groups to UI components, letting users click a category to trigger a getgroup lookup.

Stream real-time public data from Brazil's Acre state directly into your React components using the Vercel AI SDK.

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Connect Acre Dados Abertos MCP to Vercel AI SDK

Create your Vinkius account to connect Acre Dados Abertos 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 Acre Dados Abertos with Vercel AI SDK

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Instant dataset searches in your Vercel AI SDK UI

The `search_packages` tool lets your agent query Acre's public data catalog while streaming the matches directly to your user interface. Instead of waiting for a full payload, your Next.js frontend renders dataset names as they stream from the server. You configure this by calling `mcpClient.tools()` and passing them to `streamText`. Your users get immediate feedback as the agent filters through state departments using `list_organizations` to pinpoint the exact dataset they need.

Stream raw tabular records with this MCP Server

The `search_datastore` tool extracts specific rows from Acre's active datastores directly into your frontend application. This lets your AI client filter and present raw public records inside your React components without intermediate API layers. By feeding this tool into the Vercel AI SDK, raw data populates on screen while the agent explains the numbers. There are no loading spinners because the data flows chunk by chunk through the Edge-compatible transport.

Resolve dataset schemas on the fly

The `get_package` tool retrieves complete metadata schemas for any specific Acre dataset. Your agent inspects fields, resource formats, and update frequencies to prepare the UI layout before displaying the actual files. Once the layout is ready, the agent calls `get_resource` to grab specific file links. This metadata-first approach ensures your React app knows exactly how to render the incoming data stream.

Setup guide

Set up Acre Dados Abertos 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 Acre Dados Abertos 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 Acre Dados Abertos 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 Acre Dados Abertos. 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 Acre Dados Abertos MCP in Vercel AI SDK

Install `@ai-sdk/mcp` and `ai`, then use `createMCPClient` pointing to the Vinkius HTTP endpoint. Pass the tools to `streamText` and remember to call `mcpClient.close()` when the session ends to free up resources.

Yes. Use `search_datastore` to filter tabular records from the public registry. The SDK streams these rows directly to your React or Next.js frontend in real time.

The server splits queries into manageable chunks. By using `list_packages` and `get_resource` with `streamText`, your Edge Functions avoid timeout limits by flushing data to the client immediately.

Call `list_groups` to fetch the high-level categories. Your agent can then map these groups to UI components, letting users click a category to trigger a `get_group` lookup.

Vinkius runs the MCP server in an isolated sandbox. Your client only handles read-only public metadata and raw tabular records from Acre's open data portal, passing an endpoint token over HTTPS.

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