How to Use the Baserow MCP in Vercel AI SDK

Q: How do I connect Baserow to Vercel AI SDK?

Install @ai-sdk/mcp and initialize with createMCPClient. Pass the Vinkius endpoint URL and call mcpClient.tools() inside your streamText configuration. Remember to trigger mcpClient.close() when the stream finishes.

Q: Can the AI read specific table columns?

Yes, the agent runs listfields to understand the schema. It then filters the output so your frontend only receives the exact fields requested by the user.

Q: Does the Vercel AI SDK support updating Baserow rows?

Your agent handles edits by calling updaterow with the specific row ID. It only modifies the fields you pass in the JSON object, leaving the rest of the record untouched.

Stream live Baserow database records straight into your React and Next.js frontends using the Vercel AI SDK.

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Connect Baserow MCP to Vercel AI SDK

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

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Fetching records with `list_rows` and `get_row` happens instantly. Your agent pulls data from specific workspaces and feeds it directly into your frontend components. Users see the table data appearing on screen without loading spinners. You pipe the database reads straight through `streamText` so the UI updates as the AI reads.

Write user data back to tables

Handling form inputs requires `create_row` and `update_row` exposed to your edge functions. The AI maps user text into structured database fields perfectly. The client figures out the schema using `list_fields` first. It maps string responses into the correct boolean, date, or text columns automatically before committing the write.

Navigate schemas on the fly

Calling `list_databases` and `list_tables` lets your AI client find the right endpoints dynamically. Hardcoding table IDs breaks when someone changes the database structure. Views matter for filtered data. Triggering `list_views` ensures your UI only streams rows that match the pre-configured sorting rules your team set up in the no-code interface.

Setup guide

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

Install `@ai-sdk/mcp` and initialize with `createMCPClient`. Pass the Vinkius endpoint URL and call `mcpClient.tools()` inside your `streamText` configuration. Remember to trigger `mcpClient.close()` when the stream finishes.

Yes, the agent runs `list_fields` to understand the schema. It then filters the output so your frontend only receives the exact fields requested by the user.

Your agent handles edits by calling `update_row` with the specific row ID. It only modifies the fields you pass in the JSON object, leaving the rest of the record untouched.

The MCP connection handles this gracefully. Because the AI client pulls live schema data via `list_tables` before acting, it adapts to new columns without code changes.

Vinkius routes your API calls through an ephemeral V8 Isolate sandbox. When your app pulls user names and email addresses from a table, the memory wipes instantly after the request completes. No middleman stores your records.

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