How do I get a Baserow API Token?

Log in to your Baserow workspace, go to **Database Settings > API Tokens** (or Workspace Settings > API Tokens), click **Create Token**, give it a name and set the permissions (create, read, update, delete) for specific tables. Copy the token immediately — it won't be shown again.

Can I create and update rows programmatically?

Yes! Use `create_row` with the table ID and a JSON object of field_name: value pairs. Use `update_row` with the table ID, row ID and the fields to update. First use `list_fields` to discover the available field names and their types for the table.

Can I filter rows by field values?

Yes! The `list_rows` tool supports pagination and ordering. Use the `page` and `size` parameters for pagination, and `order_by` to sort by any field (prefix with `-` for descending). The underlying API also supports field-level filtering through the filter parameter.

What field types does Baserow support?

Baserow supports: text, number, boolean, date, long_text, email, url, single_select, multiple_select, link_row (relationships), file, rating, formula, lookup, rollup, last_modified and created_on fields. Use `list_fields` to see the exact types in your table.

Baserow MCP Server for Vercel AI SDK 10 tools — connect in under 2 minutes

Name: Baserow
Availability: InStock
Author: Vinkius

ai-sdk.dev/docs/ai-sdk-core/mcp

Built by Vinkius GDPR 10 Tools SDK

The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Baserow through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

typescript

import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

async function main() {
  const mcpClient = await createMCPClient({
    transport: {
      type: "http",
      // Your Vinkius token. get it at cloud.vinkius.com
      url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    },
  });

  try {
    const tools = await mcpClient.tools();
    const { text } = await generateText({
      model: openai("gpt-4o"),
      tools,
      prompt: "Using Baserow, list all available capabilities.",
    });
    console.log(text);
  } finally {
    await mcpClient.close();
  }
}

main();

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About Baserow MCP Server

Connect your Baserow databases to any AI agent and take full control of your data through natural conversation.

The Vercel AI SDK gives every Baserow tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.

What you can do

Database Discovery — List all databases and tables the token has access to with their schemas
Schema Exploration — Browse table fields (columns) with their types (text, number, boolean, date, select, etc.)
Row Operations — List, create, update and delete rows with full CRUD support
Filtered Queries — Query rows with pagination, ordering and field-based filtering
View Management — List configured views (grid, gallery, kanban, form, calendar) with their filter and sort rules

The Baserow MCP Server exposes 10 tools through the Vinkius. Connect it to Vercel AI SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Baserow to Vercel AI SDK via MCP

Follow these steps to integrate the Baserow MCP Server with Vercel AI SDK.

Install dependencies

Run npm install @ai-sdk/mcp ai @ai-sdk/openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the script

Save to agent.ts and run with npx tsx agent.ts

Explore tools

The SDK discovers 10 tools from Baserow and passes them to the LLM

Why Use Vercel AI SDK with the Baserow MCP Server

Vercel AI SDK provides unique advantages when paired with Baserow through the Model Context Protocol.

TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box

Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Baserow integration everywhere

Built-in streaming UI primitives let you display Baserow tool results progressively in React, Svelte, or Vue components

Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency

Baserow + Vercel AI SDK Use Cases

Practical scenarios where Vercel AI SDK combined with the Baserow MCP Server delivers measurable value.

AI-powered web apps: build dashboards that query Baserow in real-time and stream results to the UI with zero loading states

API backends: create serverless endpoints that orchestrate Baserow tools and return structured JSON responses to any frontend

Chatbots with tool use: embed Baserow capabilities into conversational interfaces with streaming responses and tool call visibility

Internal tools: build admin panels where team members interact with Baserow through natural language queries

Baserow MCP Tools for Vercel AI SDK (10)

These 10 tools become available when you connect Baserow to Vercel AI SDK via MCP:

create_row

Requires the table ID and a JSON object with field_name: value pairs matching the table schema. Use list_fields to discover available field names. Returns the created row with its ID and all field values. Create a new row in a Baserow table

delete_row

Provide the table ID and row ID. WARNING: this action is irreversible. Delete a row from a Baserow table

get_row

Field names are returned in user-readable format. Provide the table ID and row ID. Get a specific row from a Baserow table

get_table

Provide the table ID from list_tables. Get details for a specific Baserow table

list_databases

Each database shows its ID, name, workspace and creation date. Use this to discover available databases before querying their tables. List all Baserow databases

list_fields

Each field shows its ID, name, type (text, number, boolean, date, single_select, long_text, link_row, file, etc.), order and required status. Use this to understand the data schema before querying or creating rows. List fields (columns) of a Baserow table

list_rows

Optionally filter by field values (using user_field_names) and set page/size for pagination. Results include count, next/previous page URLs and the rows array. Use field names (not IDs) for readable results. List rows in a Baserow table

list_tables

Each table shows its ID, name, database, field count and creation date. Use this to discover the data schema before querying rows. List all tables accessible in Baserow

list_views

Each view shows its ID, name, type, filter settings and sort rules. Useful for understanding how data is organized and filtered in the UI. List views configured for a Baserow table

update_row

Requires the table ID, row ID and a JSON object with field_name: value pairs for the fields to update. Only provided fields will be modified. Use list_fields to discover available field names. Update an existing row in a Baserow table

Example Prompts for Baserow in Vercel AI SDK

Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Baserow immediately.

"List all tables in my Baserow workspace."

"Show me all rows in the Tasks table where Status is 'In Progress'."

"Create a new task called 'Review PR #234' assigned to Alice with status 'To Do'."

Troubleshooting Baserow MCP Server with Vercel AI SDK

Common issues when connecting Baserow to Vercel AI SDK through the Vinkius, and how to resolve them.

createMCPClient is not a function

Install: npm install @ai-sdk/mcp

Baserow + Vercel AI SDK FAQ

Common questions about integrating Baserow MCP Server with Vercel AI SDK.

How does the Vercel AI SDK connect to MCP servers?

Import createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.